# machine-learning in Python Reviews **Vendor:** machine-learning in Python **Category:** [Machine Learning Software](https://www.g2.com/categories/machine-learning) **Average Rating:** 4.6/5.0 **Total Reviews:** 50 ## About machine-learning in Python The "machine-learning" project by jeff1evesque is a Python-based web interface and REST API designed for performing classification and regression tasks. It provides a user-friendly platform for implementing machine learning models, making it accessible for both beginners and experienced practitioners. Key Features and Functionality: - Web Interface: Offers an intuitive graphical user interface for managing datasets, training models, and visualizing results. - REST API: Enables seamless integration with other applications, allowing for automated machine learning workflows. - Classification and Regression: Supports a variety of algorithms to handle both classification and regression problems effectively. - Documentation: Comprehensive guides and resources are available to assist users in understanding and utilizing the platform's capabilities. Primary Value and User Solutions: This project simplifies the process of deploying machine learning models by providing a cohesive environment that combines data management, model training, and result analysis. It addresses common challenges in machine learning implementation, such as the need for coding expertise and integration complexities, thereby enabling users to focus on deriving insights and making data-driven decisions. ## machine-learning in Python Pros & Cons **What users like:** - Users appreciate the **rich ecosystem of libraries** in Python, enhancing machine learning model experimentation and implementation. (10 reviews) - Users appreciate the **ease of use** in Python's machine learning, simplifying development with powerful libraries and frameworks. (8 reviews) - Users appreciate the **model variety** offered by machine learning in Python, facilitating diverse and efficient solutions. (4 reviews) - Users appreciate the **intuitive nature** of Python, which simplifies the learning and implementation of machine learning projects. (3 reviews) - Users appreciate the **high-quality libraries** in Python for their effectiveness and support in machine learning projects. (3 reviews) - Documentation (2 reviews) - Problem Solving (2 reviews) - Data Management (1 reviews) - Deployment Ease (1 reviews) - Users appreciate the **easy setup** of machine learning in Python, streamlining data preparation and exploration. (1 reviews) **What users dislike:** - Users find that the **difficult learning curve** makes it challenging to effectively use machine learning in Python. (3 reviews) - Users face **dependency issues** with conflicting versions of libraries, complicating their machine learning experience in Python. (2 reviews) - Users find the **slow performance** of machine learning in Python frustrating, especially with large data sets and dependencies. (2 reviews) - Users note the **slow speed** of machine learning in Python, mainly due to its interpreted nature and resource demands. (2 reviews) - Users note that **performance limitations** in Python can hinder large-scale machine learning tasks compared to other languages. (1 reviews) - Compatibility Issues (1 reviews) - Users find the **high cost** of licensing machine-learning in Python prohibitive for many projects and budgets. (1 reviews) - Inaccuracy (1 reviews) - Integration Issues (1 reviews) - Users express concern over the **limited algorithms supported** , which restricts their machine learning capabilities in Python. (1 reviews) ## machine-learning in Python Reviews ### 1. Streamlined Model Training with Python, Needs Faster Inference **Rating:** 4.0/5.0 stars **Reviewed by:** Dev Saran S. | Science Tutor , Mid-Market (51-1000 emp.) **Reviewed Date:** April 16, 2026 **What do you like best about machine-learning in Python?** I like machine-learning in Python because of its ease of integration, making it simple to connect to models or create additional LLMs. I appreciate how easy it is to assess TensorFlow and the benefit of building on existing frameworks rather than reinventing them. This allows me to use existing functions without having to rewrite code, which makes the workflow smooth and efficient. The setup process is straightforward, with all guidelines clearly laid out in the readme, making it very easy to get started. **What do you dislike about machine-learning in Python?** The inference process in Python for machine learning models is quite slow and could be improved. Handling inference results can be a bit inefficient, and improvements based on CPU architecture could help. It would also be helpful if the inference results could be more easily passed to applications or other tech software via APIs. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine-learning in Python lets me train models with up to 20 million parameters on my GPU, creating a smooth workflow without rewriting code. ### 2. Excellent, Versatile Machine Learning with Python and Powerful Libraries **Rating:** 4.5/5.0 stars **Reviewed by:** Prashanth B. | Research Associate, Research, Small-Business (50 or fewer emp.) **Reviewed Date:** January 14, 2026 **What do you like best about machine-learning in Python?** Machine learning with Python is excellent because it’s easy, very effective, and versatile. With libraries such as scikit-learn, TensorFlow, or PyTorch, you can develop different machine learning models. Its code is very easy to write and fun, and a vast number of people ensure that you get adequate learning materials and support to efficiently apply machine learning to solve problems. **What do you dislike about machine-learning in Python?** I do not like that the machine learning in the Python coding can sometimes work slowly in the big data because it is not the fastest coding language in the world. Additionally, it can sometimes be challenging to coordinate the coding dependencies and the different versions of the coding libraries that are applied in the machine learning in the Python coding. **What problems is machine-learning in Python solving and how is that benefiting you?** In terms of Python machine learning, some problems being addressed include predictions on trends, automating processes, recognizing patterns, and making decisions based on data. This applies to industries such as healthcare, finance, and even marketing. For me as a person, its application is appreciated as it saves time, reduces human effort, and can convert data into valuable pieces of information. ### 3. Python is at the forefront of machine learning accessibility **Rating:** 4.5/5.0 stars **Reviewed by:** David Robert L. | Chief Technical Officer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 13, 2026 **What do you like best about machine-learning in Python?** Python has fantastic libraries like scikit learn, numpy, xdgboost and pandas that make machine-learning projects easy to implement for just about any data set and project. Then there's tensorflow and PyTorch, providing an endless array of possibilities. I enjoy the intuitive python language. **What do you dislike about machine-learning in Python?** Because python is interpreted not compiled it can be slow on local machines. The price one pays for an easier development environment. I have seen there is cpython which could presumably address this but I haven't tried it. **What problems is machine-learning in Python solving and how is that benefiting you?** It is currently solving issues like price prediction, budget prediction and a variety of useful tasks that I would never have considered possible. This is invaluable for today's world. And it is doing this all under the hood, with very little input from my end, in other words, having access to the raw power of Xdgboost for instance, provides an amazing tool for programmers. ### 4. Python Makes Machine Learning Accessible and Fast to Learn **Rating:** 4.5/5.0 stars **Reviewed by:** Akshit K. | Consultant, Enterprise (> 1000 emp.) **Reviewed Date:** March 13, 2026 **What do you like best about machine-learning in Python?** Machine Learning in Python has made machine learning very accessible. Python has tons of libraries that get updated frequently and also has easy implementation. This help me learn rapidly and keep up the pace with the AI advancements. **What do you dislike about machine-learning in Python?** Since a lot of Machine Learning has pivoted to Generative AI, the limitation now is the system rather than the technology. The only downside is there is limited access to good hardware where we can run machine learning in python. **What problems is machine-learning in Python solving and how is that benefiting you?** I work as a AI engineer and GenAI architect. So machine learning in python is my driver and solution for all the applications I develop and the projects I work on. ### 5. Strong Community and Libraries Make Python Great for RAG Development **Rating:** 4.5/5.0 stars **Reviewed by:** balram t. | Ai developer, Enterprise (> 1000 emp.) **Reviewed Date:** April 23, 2026 **What do you like best about machine-learning in Python?** Python has a strong community and all kinds of libraries that can connect everything, work with databases, and let you use ML algorithms depending on the use case. I’m really enjoying Python while developing RAG-based systems. **What do you dislike about machine-learning in Python?** I don’t have anything bad to say about Python; it’s just that sometimes it can be slow, depending on the system and the process. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine learning helps solve many problems, such as ticket priority recommendations, ticket resolution, RAG-based systems, and more, using Python and its libraries. ### 6. Efficient Machine Learning Development Using Python Ecosystem **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Accounting | Small-Business (50 or fewer emp.) **Reviewed Date:** March 15, 2026 **What do you like best about machine-learning in Python?** I like machine learning in Python because it combines simplicity with a powerful ecosystem. Libraries like NumPy, Pandas, and Scikit-learn make data processing, model building, and evaluation efficient. Python’s readability and strong community support also allow faster experimentation and development of ML solutions. **What do you dislike about machine-learning in Python?** drawback of machine learning in Python is performance limitations for very large-scale computations and sometimes complex dependency management across libraries. Since Python is interpreted, it can be slower than lower-level languages. However, most ML frameworks solve this with optimized backends and GPU support, which keeps Python highly effective for ML development. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine learning in Python helps solve problems like data prediction, pattern recognition, and automation of complex tasks. Its rich ecosystem of libraries allows quick model development and data analysis. This benefits me by enabling faster experimentation, building intelligent features, and turning large datasets into actionable insights ### 7. Powerful for Solving New and Community Problems **Rating:** 4.0/5.0 stars **Reviewed by:** Shubham V. | Student, Small-Business (50 or fewer emp.) **Reviewed Date:** January 15, 2026 **What do you like best about machine-learning in Python?** It helps us solve problems, whether they’re community-related or entirely new issues—much like saving old handwritten palm leaf manuscripts, a project I handled myself. **What do you dislike about machine-learning in Python?** It does come with a heavy set of prerequisites, like learning Python, understanding the basics of machine learning, the different models and their metrics, and a lot more. **What problems is machine-learning in Python solving and how is that benefiting you?** It helps solve new problems and automate tasks in a way that’s tailored to us as individuals, rather than generalising everything. We can let machines take the time and use data to understand us better, learn our routines, and then make more relevant suggestions that can help in ways we might not even expect. ### 8. Production-Grade Machine Learning in Python with Powerful Libraries **Rating:** 5.0/5.0 stars **Reviewed by:** KharanKumar R. | Data Analyst, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** January 20, 2026 **What do you like best about machine-learning in Python?** Machine-learning in python have very good libraries like sklearn, tensorflow and pandas, numpy more and more which are really helpful and production grade model building capability it have. **What do you dislike about machine-learning in Python?** I don't have anything to dislike about machine-learning in python everything based on requirement it is good. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine-learning in python is solving my problem by reducing code and using libraries of machine-learning models also like knn, xboost, svm like more and benefiting by building good model for classification and regression. ### 9. AI learning with python **Rating:** 5.0/5.0 stars **Reviewed by:** Shivani S. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 13, 2026 **What do you like best about machine-learning in Python?** In today’s environment, we use Artificial Intelligence (AI) in our daily activities, and Machine Learning (ML) is a part of AI. Nowadays, many people want to learn Machine Learning, and Python is one of the best languages for this purpose because: 1. It has so many libraries, 2. It supports strong community. 3. It is easy to learn language. 4. Used in so many IT industries. **What do you dislike about machine-learning in Python?** I don’t have anything to dislike about Machine Learning in Python because I am currently learning it and find it interesting. **What problems is machine-learning in Python solving and how is that benefiting you?** In an AI-driven society, we are becoming stronger in technology and learning advanced concepts through Machine Learning. ### 10. Python ML Made Easy with Vast Libraries and GPU Support **Rating:** 4.0/5.0 stars **Reviewed by:** Sahil P. | AIML Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 13, 2026 **What do you like best about machine-learning in Python?** In Python, the availability of vast prebuilt libraries and GPU support makes development and deployment much easier. This helps streamline the overall process, from building to putting solutions into use. **What do you dislike about machine-learning in Python?** I haven’t had many problems doing machine learning in Python; it’s my go-to language for it. **What problems is machine-learning in Python solving and how is that benefiting you?** Developing solutions like this feels as if it has a mind of its own, helping us tackle complexity at scale. It enables us to automate decision-making processes that are too complex and dynamic for traditional programming approaches. Solving real-world issues is what makes this such a useful tool. ### 11. Great Platform for Python Libraries and Machine Learning Workflows **Rating:** 4.5/5.0 stars **Reviewed by:** Prathamesh B. | intern, Small-Business (50 or fewer emp.) **Reviewed Date:** February 07, 2026 **What do you like best about machine-learning in Python?** The ability to utilise this platform and make it work with Python libraries that support the machine algorithm is great. **What do you dislike about machine-learning in Python?** The only issue is that it takes time to get used to it, especially figuring out how to comment the code. Sometimes it also feels hard to work with. **What problems is machine-learning in Python solving and how is that benefiting you?** The solution I get is that I have a reliable platform to showcase my algorithm and the ability to share it with others, in an open-source sense. ### 12. Machine Learning Fundamentals That Build Strong Models **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) **Reviewed Date:** January 16, 2026 **What do you like best about machine-learning in Python?** Machine learning is a fundamental topic for learning how to build models and help a machine learn from its experiences. Need to add i was a stundent 2025 passout from VIT bhopal unversity specialised in AIML.Hence I well know about the number of alogorithms and usage they are easy to Integrated then other deep learning algoritms. **What do you dislike about machine-learning in Python?** Everyone has started moving toward deeper learning techniques.But machine learning algorithms are easiest to use so far and can be remodified and hypertuned frquently. **What problems is machine-learning in Python solving and how is that benefiting you?** I use it to build different models for disease prediction, data analysis, classification etc and many other tasks. ### 13. Python: The Go-To Language for Accessible, High-Performance Machine Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Jordas N. | Translator and interpreter, Small-Business (50 or fewer emp.) **Reviewed Date:** January 13, 2026 **What do you like best about machine-learning in Python?** You can manage data effectively and understand different processes. **What do you dislike about machine-learning in Python?** Python is excellent for learning, experimentation, and the majority of production machine learning tasks. However, as projects grow in scale, Python can sometimes feel fragile, inefficient, or unnecessarily complex. In these situations, languages such as C++, Java, or Rust are often used to handle the most critical components. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine learning in Python helps solve the challenge of turning data into scalable, adaptive intelligence. It benefits me by making my work faster, smarter, and more impactful—whether I’m analyzing data, building systems, or making decisions. ### 14. Python Makes Machine Learning Feel Creative **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** January 18, 2026 **What do you like best about machine-learning in Python?** Python makes machine learning feel creative rather than painful. **What do you dislike about machine-learning in Python?** Version conflicts between NumPy, CUDA, PyTorch, TensorFlow, and OS drivers can be brutal **What problems is machine-learning in Python solving and how is that benefiting you?** Machine learning in Python solves problems like pattern recognition, prediction, and automation by turning large, messy data into useful insights. ### 15. Promising Emerging Technology with Continuous Improvements **Rating:** 4.5/5.0 stars **Reviewed by:** Ayushi S. | Technical Associate, Enterprise (> 1000 emp.) **Reviewed Date:** January 16, 2026 **What do you like best about machine-learning in Python?** Since it’s an emerging technology, there are still many areas where improvements are being made and used. **What do you dislike about machine-learning in Python?** It can store personal data to help the agent learn. **What problems is machine-learning in Python solving and how is that benefiting you?** As a software engineer, I find it helpful for solving analytical thinking problems. ### 16. Pandas With Pyton **Rating:** 4.5/5.0 stars **Reviewed by:** Komal A. | Spec Analytics, Enterprise (> 1000 emp.) **Reviewed Date:** January 22, 2025 **What do you like best about machine-learning in Python?** I like that Python offers a rich ecosystem of libraries like TensorFlow, scikit-learn, and PyTorch, making it easy to implement and experiment with machine learning models efficiently. **What do you dislike about machine-learning in Python?** I dislike that machine learning in Python can sometimes be resource-intensive, requiring significant computational power for training large models. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine learning in Python is solving the problem of automating data-driven decision-making and predictive analytics, benefiting me by enabling the development of efficient models for diverse applications like forecasting and classification. ### 17. Director of Engineering - Oracle **Rating:** 4.0/5.0 stars **Reviewed by:** Mikhail I. | Director of Software Engineering, Enterprise (> 1000 emp.) **Reviewed Date:** December 04, 2024 **What do you like best about machine-learning in Python?** - Makes Data Preparation and exploration easy, specially at initial stage - No need for data extraction. Can work with the data in DB - Pipeline is simple **What do you dislike about machine-learning in Python?** - Limited algorithms supported - Cost, due to license **What problems is machine-learning in Python solving and how is that benefiting you?** Python is ver popular language now. While keeping data in DB, no need for extraction steps, we can do complete POC for supervised, classification, bag of words, ... solutions for data in DB. Without doing ETL, we currently are able to do some supervised learning solutions for data in Oracle DB using OML4Py ### 18. My review on machine learning with python **Rating:** 5.0/5.0 stars **Reviewed by:** Kunal M. | Data analysts, Mid-Market (51-1000 emp.) **Reviewed Date:** August 21, 2024 **What do you like best about machine-learning in Python?** The thing I like best about machine learning with python is it provides extensive libraries and framework which make our work easy. It's has one of the best community support for coders. Best for visualization with help of Matplotlib as Seaborn... **What do you dislike about machine-learning in Python?** Currently there is nothing which I see I dislike about machine learning with python. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine learning in Python has addressing a wide range of problems across various domains, and its benefits are substantial in fields like finance, Healthcare, manufacturing production and nature language processing and also transportation... ### 19. "Python: The Ideal Language for Machine Learning " **Rating:** 5.0/5.0 stars **Reviewed by:** Shivam M. | Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** June 02, 2023 **What do you like best about machine-learning in Python?** Since Python is a very easy langauge and for machine learning, we have to write a large, diverse, and very complex code which is quite difficult in any other programing language so from that point python is the best suitable language for machine learning. Also, it has huge libraries that help developers to write code efficiently and effectively. **What do you dislike about machine-learning in Python?** As a machine-learning engineer, I have found Python to be an amazing machine-learning language, and I value its adaptability and breadth of features. Python is well-known not only for its success in machine learning and data science but also as a top choice for web development and other disciplines. Its extensive library ecosystem, user-friendly syntax, and lively community make it a favorite language for developers, enabling them to design new and efficient solutions. Python actually shines at providing a smooth and engaging experience for both machine learning practitioners and fans. **What problems is machine-learning in Python solving and how is that benefiting you?** The use of machine learning in Python has contributed to the creation of powerful tools and libraries that have enabled the development of more advanced and sophisticated AI models like chat gpt. It provides efficient and scalable solutions to complex problems, helps in automating tasks, enhances decision-making processes, enables data-driven insights, and opens up opportunities for innovation and competitive advantage. Python's rich ecosystem of libraries, extensive documentation, and active community further support practitioners in building and deploying machine learning models effectively. ### 20. It's important to know and apply **Rating:** 4.5/5.0 stars **Reviewed by:** Prasanth B. | Process Specialist, Small-Business (50 or fewer emp.) **Reviewed Date:** October 19, 2023 **What do you like best about machine-learning in Python?** Pandas - I love to explore the data with pandas **What do you dislike about machine-learning in Python?** At times simple task we need to follow the sane steps **What problems is machine-learning in Python solving and how is that benefiting you?** Predictions ### 21. Data Mining for machine Learning **Rating:** 4.5/5.0 stars **Reviewed by:** Syed Adeel H. | Infrastructure Manager, Small-Business (50 or fewer emp.) **Reviewed Date:** March 29, 2023 **What do you like best about machine-learning in Python?** One of the key benefits of using Python for machine learning is its ease of use. The language has a clean and intuitive syntax that makes it easy to write and understand code, even for those who are new to programming. Additionally, Python has a large and supportive community that provides plenty of resources and tutorials to help users get started. **What do you dislike about machine-learning in Python?** Python is an interpreted language, which means that it is slower than compiled languages like C++ or Java. This can be a disadvantage when working with very large datasets or complex algorithms. **What problems is machine-learning in Python solving and how is that benefiting you?** With the help of Python Machine learning it can be used to detect fraudulent transactions, such as credit card fraud. Python libraries such as sci-kit-learn and TensorFlow is used to build fraud detection models that can identify patterns of fraudulent behavior. ### 22. Super quick to get going, great results **Rating:** 4.5/5.0 stars **Reviewed by:** Oliver G. | Technical Sales Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** June 28, 2022 **What do you like best about machine-learning in Python?** Very well supported tools like tensorflo **What do you dislike about machine-learning in Python?** Performance can be problematic and hard to diagnose, especially with by default using 100% of any gpu given **What problems is machine-learning in Python solving and how is that benefiting you?** I used tensorflow for academic research for classification based on images and point data. We achieved results not possible with traditional coding tools ### 23. Python for Machine Learning (Model Development & Deployment) **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Management Consulting | Small-Business (50 or fewer emp.) **Reviewed Date:** November 12, 2021 **What do you like best about machine-learning in Python?** Python is the most advanced programming language for implementing machine learning models from scratch. It provides a vast range of libraries and custom functions for building, training, and developing ML models. It offers easily interpretable, reasonable, and concise code and allows developers to build and test complex machine learning algorithms on structured and unstructured data with ease. **What do you dislike about machine-learning in Python?** Python is an interpreted programming language that has limited speed since code execution occurs line by line. Threading is not supported in Python, which serves as an issue while implementing ML solutions at scale. **Recommendations to others considering machine-learning in Python:** I would definitely recommend using Python for building machine-learning-based applications, provided your team has the expertise in coding. Python requires developers to be familiar with the concept of functions, classes and object oriented programming. **What problems is machine-learning in Python solving and how is that benefiting you?** We are using python in multiple projects for building machine-learning solutions from scratch. It helped the developers to quickly train and test the ML models on structured data for building risk-based scorecards. Scikit-learn library provides all the algorithms for implementing machine-learning models such as Random Forest, XGBoost, SVM, Linear and Logistic Regression. We also use Python for automating processes that involve manual screening and verification. ### 24. It is very easy to create machine learning model with the help of several python library . **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Design | Enterprise (> 1000 emp.) **Reviewed Date:** May 19, 2022 **What do you like best about machine-learning in Python?** Creating a machine learning model with the help of python is very easy, also if you are integrating it with synchronous pipeline python works very well. **What do you dislike about machine-learning in Python?** I can only think of a little slow otherwise everything is good. **Recommendations to others considering machine-learning in Python:** for Machine learning use cases I couldn't think of any other language than Python. **What problems is machine-learning in Python solving and how is that benefiting you?** Machine learning model creation to identify the element, semantic segmenatation, etc. ### 25. Powerful and modern machine-learning using python **Rating:** 5.0/5.0 stars **Reviewed by:** Alvaro R. | Profesor titular, Mid-Market (51-1000 emp.) **Reviewed Date:** June 17, 2021 **What do you like best about machine-learning in Python?** The last and more advanced models for machine learning are available in python. This allows you to perform up-to-date experiments. There are a lot of tutorials for using machine learning with python and the most modern systems use it. If I have any problem with the output, or any error, there are a lot of internet forums showing any possible solution. That encourages me to use it because I can be sure of solving any problem I may have. If you do not find the solution, you can post a question and wait for an answer in the next days. On the other hand, machine learning with python allows using HW acceleration such as GPUs. You only need to set the proper HW. Another advantage is the fact that there are several libraries for doing machine learning with python. In case you do not like any, you can choose among the others. **What do you dislike about machine-learning in Python?** There are multiple libraries and the documentation for some of them is sometimes incomplete. Besides, some functions change from different versions, making old code incompatible with new code. **Recommendations to others considering machine-learning in Python:** If you already know what algorithm you want to use, you only need to search for the name of that algorithm in the library. If you have any doubt, I suggest to take a look at the API or any examples in the web. **What problems is machine-learning in Python solving and how is that benefiting you?** I mostly work with text classification and other tasks related to natural language processing. I can process text with other python tools and connect the output to any machine learning model. ### 26. Best open source platform to perform Analytics **Rating:** 5.0/5.0 stars **Reviewed by:** Dinesh Y. | Manager, Enterprise (> 1000 emp.) **Reviewed Date:** December 30, 2021 **What do you like best about machine-learning in Python?** It's available on open-source platform & have a very good community for clarifying all the doubts **What do you dislike about machine-learning in Python?** Data security is one of the concerns here, but there's a lot of ways to protect it. **What problems is machine-learning in Python solving and how is that benefiting you?** Predicting the sales of card members in the upcoming months & accordingly planning for the marketing budget. ### 27. Machine learning with python **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** January 15, 2022 **What do you like best about machine-learning in Python?** It will reduce our work drastically. Example: last month I worked on text summarisation with ml at the end of the project I concluded it reduces 80% of our manual effort. **What do you dislike about machine-learning in Python?** There is a drawback that it is not accurate sometime **What problems is machine-learning in Python solving and how is that benefiting you?** As I mentioned in above, i worked on text summarisation so at the end I realised it reduces lots of manual effort ### 28. Python- scripting tool and machine learning tool **Rating:** 4.0/5.0 stars **Reviewed by:** manisha s. | intern, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** July 29, 2020 **What do you like best about machine-learning in Python?** Python is easy to use machine learning programming language which have extensive libraries and packages .Its packages provide efficient visualization to understand .Also nowadays used for cyber security purpose for automated scripting **What do you dislike about machine-learning in Python?** Syntax is less user friendly comparatively to other machine programming languages like R which makes it less efficient for beginners . **Recommendations to others considering machine-learning in Python:** Its best programming language to cater any algorithm needs and has been growing daily through deep learning and AI . **What problems is machine-learning in Python solving and how is that benefiting you?** It really helped me to code better any kind of machine learning algorithm ### 29. ML in python **Rating:** 4.5/5.0 stars **Reviewed by:** Kartik K. | Product Technology Planning- Staff Industrial Engineer, Global Operations, Enterprise (> 1000 emp.) **Reviewed Date:** September 15, 2020 **What do you like best about machine-learning in Python?** Compatibility with dataframes and online community. Also its easy to learn and easy to use **What do you dislike about machine-learning in Python?** Less flexibility on changing the algorithm. Modify libraries is not that easy **Recommendations to others considering machine-learning in Python:** Its easy to learn and ease of use make it great **What problems is machine-learning in Python solving and how is that benefiting you?** I am solving prediction models and its helping me automate and sometimes optimizing the problem based on previous data ### 30. Positive feedback on Python Machine Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Business Supplies and Equipment | Enterprise (> 1000 emp.) **Reviewed Date:** July 29, 2020 **What do you like best about machine-learning in Python?** The fact its operates on a simplified route. **What do you dislike about machine-learning in Python?** Sometimes the error code can be difficult to identify **Recommendations to others considering machine-learning in Python:** I would say everyone should try this out, and I strongly believe that you will also recommend this for others **What problems is machine-learning in Python solving and how is that benefiting you?** Currently am working on designing a component that can be added to an already existing system. Machine-learning in Python make the coding of the component easy, because we would just have to most time copy and past to see the required result. ### 31. Machine Learning Era **Rating:** 4.5/5.0 stars **Reviewed by:** Prabakar S. | Project Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** April 13, 2019 **What do you like best about machine-learning in Python?** Packages like Sci-kit learn and Keras are very useful for fast deployment in the production line. Deep Learning in computer vision shows a considerable result. With a huge amount of data, Python Machine Learning frameworks help us to develop faster and reduce our development time. Frameworks like Tensorflow, caffe, pytorch are very effective in deep learning development and deployment. **What do you dislike about machine-learning in Python?** When we have a large amount of dataset, it is necessary to analyze it before we use it for development. Here in Python Machine Learning, there is no good data analysis framework in python. I dislike python because it's development time is very high. **Recommendations to others considering machine-learning in Python:** Good tool. **What problems is machine-learning in Python solving and how is that benefiting you?** We use machine learning in quality analysis. Earlier we used custom algorithms for finding defects on a product in the production line. After getting into python machine learning all the features are learned by the framework itself, we only need to make sure the data we give in is unbiased. The development burden is reduced a lot. Now we are focussing on making better hardware for our products. ### 32. One of the best library for implementing machine learning **Rating:** 5.0/5.0 stars **Reviewed by:** Neha S. | Software Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** August 02, 2018 **What do you like best about machine-learning in Python?** It's amalgamation of all sorts of machine learning algorithms along with their examples and tutorials is the best thing. It is very well documented which makes it easy to implement. It is also user friendly. **What do you dislike about machine-learning in Python?** It has provided many methods of implementation which is quite good but arises too much confusion at the same time. So one needs to do some research as to which one to select among the available options. **Recommendations to others considering machine-learning in Python:** Machine learning in python is one full package of great libraries one of which is "scikit-learn". Along with it has provided all sorts of useful examples as well as tutorials which makes us easy for implementing machine learning. **What problems is machine-learning in Python solving and how is that benefiting you?** It has helped quite a lot in research works related to data mining and also in big data analysis. We could train our data with the different algorithms available and so were able to judge the accuracy. The most important usage is of the "scikit-learn" library. ### 33. The simplicity of using python for machine learning **Rating:** 5.0/5.0 stars **Reviewed by:** Bryce S. | Machine Learning Engineer, Wireless, Small-Business (50 or fewer emp.) **Reviewed Date:** October 13, 2018 **What do you like best about machine-learning in Python?** I like how simple python is to use as well as the amount of libraries that are already jn existence to help with reducing the time of development. **What do you dislike about machine-learning in Python?** The only thing I really dislike is when they update the version of python and you are left with codes that work only on certain versions. This becomes your job to then update or reduce the code syntax depending on the version you are using. **What problems is machine-learning in Python solving and how is that benefiting you?** I am using Python in order to classify specific images and also to localize specific objects. ### 34. Great Language for Machine Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Rajat W. | Process Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** November 13, 2018 **What do you like best about machine-learning in Python?** A lot of modules available for machine learning, just have to prepare the data as per the requirement and then the modules take care of algorithm **What do you dislike about machine-learning in Python?** Preparation of data for training the algorithm **What problems is machine-learning in Python solving and how is that benefiting you?** Great way to automate processes and analysis of data. Also helps to predict a lot of values. ### 35. Train and gain **Rating:** 5.0/5.0 stars **Reviewed by:** Daud K. | Laboratory Specialist, Hospital & Health Care, Enterprise (> 1000 emp.) **Reviewed Date:** August 08, 2018 **What do you like best about machine-learning in Python?** It’s said that training a network is very hard on machine learning, but if do same through python, it becomes easier. Try , you will get amazed **What do you dislike about machine-learning in Python?** There is nothing I dislike about doing machine learning in python **What problems is machine-learning in Python solving and how is that benefiting you?** Currently analyzing genome data using python machine learning and trying to build some algorithm that could detect the genetic variant ### 36. Machine Learning with Python Pandas **Rating:** 4.5/5.0 stars **Reviewed by:** James S. | Mid-Market (51-1000 emp.) **Reviewed Date:** August 03, 2018 **What do you like best about machine-learning in Python?** Its easy to use. Lots of documentation online. **What do you dislike about machine-learning in Python?** Currently, nothing. I prefer it to Matlab or R. **Recommendations to others considering machine-learning in Python:** Learn and use it as much as you can. This is definitely going to be used in the future as well. **What problems is machine-learning in Python solving and how is that benefiting you?** It depends what comes my way. I have done forecasting of stocks, developed churn prediction models for retail industry. ### 37. Machine learning in python can be used by even the most technologically challenged! **Rating:** 4.0/5.0 stars **Reviewed by:** Savannah L. | Post-Baccalaureate IRTA, Research, Enterprise (> 1000 emp.) **Reviewed Date:** July 30, 2018 **What do you like best about machine-learning in Python?** There are so many well-documented, common-sense, easily implementable python scripts and packages for machine learning. Scikit learn has some amazing tutorials, for concept learning, function learning or “predictive modeling”, and clustering and finding predictive patterns. With the language of python itself, it is easy to understand how to utilize the Kmeans algorithm, and implement aspects of machine learning with your own data. **What do you dislike about machine-learning in Python?** Getting started can be difficult! Tutorials can be hard to find, especially if you aren't used to using open-source languages like python. **What problems is machine-learning in Python solving and how is that benefiting you?** Big data analysis to measure outcomes for our smartphone app intervention ### 38. Machine Learning using Python **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Aviation & Aerospace | Enterprise (> 1000 emp.) **Reviewed Date:** October 03, 2018 **What do you like best about machine-learning in Python?** Python is one of the most popular programming languages for solving the problems associated with machine learning. Python libraries like Keras, Theanos, TensorFlow, and Scikit-Learn have made programming machine learning relatively easy. **What do you dislike about machine-learning in Python?** Sometimes because of data Python IDE gets hanged. **Recommendations to others considering machine-learning in Python:** Machine learning is best used in Python because of ML libraries and especially for data visualization. **What problems is machine-learning in Python solving and how is that benefiting you?** I use machine learning to build classification models to solve industrial problems. I have realized that it is easy to interpret and understandable. Easy to create a confusion matrix which is used for getting classification accuracy. ### 39. Easy to learn, many resource = efficient! **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Medical Practice | Mid-Market (51-1000 emp.) **Reviewed Date:** July 13, 2018 **What do you like best about machine-learning in Python?** Machine learning with Python is very much easy to set up. Once you have download Python, assuming if you download with Spyder and Anaconda, everything will be pre-packaged. For people with amataeur coding knowledge like me, whenever I hit a brick wall, I’m able to go online and find solutions. **What do you dislike about machine-learning in Python?** Unlike Tableau, there is no official platform, at least I couldn’t find one. Plus there’s way too many packages for machine learning. You need to do your research to know which is suitable for your scenario. **What problems is machine-learning in Python solving and how is that benefiting you?** Natural lanaguage processing, text classification. ### 40. Best Library for Machine Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Amirreza S. | Research Assistant, Mid-Market (51-1000 emp.) **Reviewed Date:** March 29, 2018 **What do you like best about machine-learning in Python?** Given the huge amount of investment different companies have made on python for machine learning there are really nice tools available for all sort of machine learning algorithms in python. Almost every deep neural network framework is written mainly for Python or has a Python wrapper. SciPy Library provides all you need to do most of the basic machine learning algorithms work. **What do you dislike about machine-learning in Python?** Unlike MATLAB different companies are developing tools for Python. There are always new libraries that are incompatible with others. I usually don't upgrade to a new version of a library until I something stops working. **Recommendations to others considering machine-learning in Python:** If you are familiar with basic of OO programming. Using Python machine-learning tools should be easy for you. **What problems is machine-learning in Python solving and how is that benefiting you?** We train different machine learning algorithm for computer vision applications. ### 41. It really easy running machine learning applications using python **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** April 03, 2018 **What do you like best about machine-learning in Python?** scikit-learn package included with most of efficient and recent machine learning tools such as Random Forest, SVM, Boosting and so on. Its really easy and fast with python scikit-learn package. **What do you dislike about machine-learning in Python?** You just need basic coding skills in python. Once you are familiar with python coding which is pretty easy, machine learning applications are piece of cake using python. **What problems is machine-learning in Python solving and how is that benefiting you?** I have used mostly in my research work related to data mining and signal processing. ### 42. Python is one of the best tools for machine learning **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) **Reviewed Date:** August 01, 2018 **What do you like best about machine-learning in Python?** Tensor flow tool for deep learning. This is the best thing I like about python as it offers so much flexibility for deep learning **What do you dislike about machine-learning in Python?** I find debugging a little tedious sometimes. **Recommendations to others considering machine-learning in Python:** Great for deep learning tools **What problems is machine-learning in Python solving and how is that benefiting you?** Recognition problems. Python offers a bunch of libraries. ### 43. Extensive machine learning libraries and tools **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** March 20, 2018 **What do you like best about machine-learning in Python?** Comprehensive collections of machine learning algorithms and lots of examples and tutorials, in particular scikit-learn library have almost every possible machine learning algorithm included **What do you dislike about machine-learning in Python?** Documentation for some functions is rather limited. Not every implemented algorithm is present. Most of the additional libraries are easy to install but some can be quite cumbersome and take a while. **Recommendations to others considering machine-learning in Python:** Machine learning in Python have lots of great libraries, check out tutorials for each module before using it as it usually has lots of useful examples. **What problems is machine-learning in Python solving and how is that benefiting you?** Unsupervised clustering and classification. The most popular library scikit-learn (or sklearn) have a collection of examples and tutorials that can be easily followed. Other modules are easy to install. ### 44. Machine Learning with Python **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Telecommunications | Mid-Market (51-1000 emp.) **Reviewed Date:** August 03, 2018 **What do you like best about machine-learning in Python?** Ease of Setup, plethora of options, tutorials, blogs, resources available, Ease of start **What do you dislike about machine-learning in Python?** Nothing. It is great. Because everything is open source, finding support or help can be a bit tricky for custom problems. **Recommendations to others considering machine-learning in Python:** There are great courses available online. Pick one. Get started. Buy some cloud space if you don't have processing power, find a project on Kaggle and just get started **What problems is machine-learning in Python solving and how is that benefiting you?** Multiple things. Trying sentiment detection, voice profiling, NLP on phonecalls ### 45. Python - The easiest way to get your hands dirty in machine learning **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** July 30, 2018 **What do you like best about machine-learning in Python?** The ease of implementation that python libraries offer and available documentation. **What do you dislike about machine-learning in Python?** Too many ways to implement the same thing, sometimes ot becomes confusing. **Recommendations to others considering machine-learning in Python:** Start with the basic iris dataset classification problem. **What problems is machine-learning in Python solving and how is that benefiting you?** I solve a lot of classification and regression problems with scikit learn library. A well explained documentation is available online. There are many websites for beginners. With just a few lines of code you can train your own Machine learning model. ### 46. no comments **Rating:** 2.5/5.0 stars **Reviewed by:** Chinmaya L. | Research Assistant, Hospital & Health Care, Small-Business (50 or fewer emp.) **Reviewed Date:** August 04, 2018 **What do you like best about machine-learning in Python?** It is easy to learn and improve your coding skills. **What do you dislike about machine-learning in Python?** Sometimes the code is incomplete and therefore the project remains incomplete. **What problems is machine-learning in Python solving and how is that benefiting you?** Learning from someone else's code. ### 47. Well advanced software **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** August 06, 2018 **What do you like best about machine-learning in Python?** It's exactly what it's supposed to be. Python is one of the best coding languages out there still to this day and this software makes it so much easier to test. **What do you dislike about machine-learning in Python?** Honestly, nothing really to dislike about this software. **What problems is machine-learning in Python solving and how is that benefiting you?** I am able to automate a lot of the testing that I would spend hours on end to complete. ### 48. Best Open-Source Tool Out For Machine Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Internet | Mid-Market (51-1000 emp.) **Reviewed Date:** August 02, 2018 **What do you like best about machine-learning in Python?** Everything. Python is the most production friendly, scalable fast, object oriented, open source language with best support in the world to build machine learning model in the industry **What do you dislike about machine-learning in Python?** There is nothing which I don't like about Python **Recommendations to others considering machine-learning in Python:** Go for it. Hands Down! **What problems is machine-learning in Python solving and how is that benefiting you?** Building Production grade machine learning model within the company for many many projects. ### 49. great ML functions **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** May 18, 2018 **What do you like best about machine-learning in Python?** available build in functions open-source free available tutorial and learning material online **What do you dislike about machine-learning in Python?** slight learning curve if a transition from another language **Recommendations to others considering machine-learning in Python:** you only need to know the higher level programming language to use it very easy to learn python is the new R if you are in DS field **What problems is machine-learning in Python solving and how is that benefiting you?** medical and disease classifications diagnosis prediction it's quick to run ML algorithms in python ### 50. ML in Python review **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** January 31, 2018 **What do you like best about machine-learning in Python?** Gradient descent and Linear regression model **What do you dislike about machine-learning in Python?** It takes more time to execute the code, but the ide is really helpful, that is what i like about this software. **What problems is machine-learning in Python solving and how is that benefiting you?** I am making machine to learn more with this. ## machine-learning in Python Discussions - [Which Python version is best for machine learning?](https://www.g2.com/discussions/which-python-version-is-best-for-machine-learning) - 2 comments - [What is Python with machine learning?](https://www.g2.com/discussions/what-is-python-with-machine-learning) - 1 comment - [View machine-learning in Python pricing details and edition comparison](https://www.g2.com/products/machine-learning-in-python/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-05+07%3A32%3A13+-0500&secure%5Bsession_id%5D=bdb15bfb-b12b-44a3-81fc-a6cf48fbdd9e&secure%5Btoken%5D=51d71a9cc950b609356a74b5d760a09c6a9f59f55dd39c7f861e79dd7f36f475&format=llm_user) ## machine-learning in Python Integrations - [AWS CloudFormation](https://www.g2.com/products/aws-aws-cloudformation/reviews) - [AWS Lambda](https://www.g2.com/products/aws-lambda/reviews) - [Azure AI Document Intelligence](https://www.g2.com/products/azure-ai-document-intelligence/reviews) - [Docusign Gen](https://www.g2.com/products/docusign-gen/reviews) - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - [MySQL 5.6](https://www.g2.com/products/mysql-5-6/reviews) - [ServiceNow IT Service Management](https://www.g2.com/products/servicenow-it-service-management/reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - [Visual Studio Code](https://www.g2.com/products/visual-studio-code/reviews) ## machine-learning in Python Features **Integration - Machine Learning** - Integration **Learning - Machine Learning** - Training Data - Actionable Insights - Algorithm ## Top machine-learning in Python Alternatives - [Weka](https://www.g2.com/products/weka/reviews) - 4.3/5.0 (13 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (779 reviews) - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (650 reviews)