--- title: machine-learning in Python Reviews meta_title: 'machine-learning in Python Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 51 reviews by the users' company size, role or industry to find out how machine-learning in Python works for a business like yours. aggregate_rating: rating_value: 4.6 review_count: 51 scale: '5' date_modified: '2026-07-17' parent_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # 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:** 51 ## 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 love the **rich ecosystem of libraries** in Python that enhance machine learning model development and experimentation. (10 reviews) - Users appreciate the **ease of use** in Python for machine learning, simplifying development with powerful libraries and tools. (8 reviews) - Users value the **model variety** in Python's machine learning libraries, enabling diverse and effective solutions for various problems. (4 reviews) - Users appreciate the **intuitive nature** of Python for machine learning, making it easy to learn and apply. (3 reviews) - Users love the **robust libraries** in Python machine learning, enhancing model building and simplifying data preparation. (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 **difficult learning** curves due to prerequisites and confusing aspects, making initial usage challenging. (3 reviews) - Users face significant **dependency issues** with version conflicts and library coordination, complicating their machine learning experience. (2 reviews) - Users experience **slow performance** with machine learning in Python, especially when handling large datasets and dependencies. (2 reviews) - Users find the **slow speed** of machine learning in Python frustrating, particularly during resource-intensive model training. (2 reviews) - Users note that **performance limitations** in Python can hinder large-scale, compute-intensive machine learning tasks. (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. 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. ### 3. 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. ### 4. 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 ### 5. 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 ### 6. 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 ## 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?filters%5Bnps_score%5D%5B%5D=4§ion=pricing&secure%5Bexpires_at%5D=2026-07-20+14%3A34%3A09+-0500&secure%5Bsession_id%5D=35b8a47e-3d4e-48d8-9721-bea1eae8b43a&secure%5Btoken%5D=847814f166eae48c243ae0329ad6652ce6696c2e26f37bf2343db734b357e049&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) - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (654 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (845 reviews)