--- title: Azure Machine Learning Reviews meta_title: 'Azure Machine Learning Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 90 reviews by the users' company size, role or industry to find out how Azure Machine Learning works for a business like yours. aggregate_rating: rating_value: 4.3 review_count: 90 scale: '5' date_modified: '2026-07-17' parent_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # Azure Machine Learning Reviews **Vendor:** Microsoft **Category:** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) **Average Rating:** 4.3/5.0 **Total Reviews:** 90 ## About Azure Machine Learning Azure Machine Learning is an enterprise-grade service that facilitates the end-to-end machine learning lifecycle, enabling data scientists and developers to build, train, and deploy models efficiently. Key Features and Functionality: - Data Preparation: Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric. - Feature Store: Increase agility in shipping your models by making features discoverable and reusable across workspaces. - AI Infrastructure: Take advantage of purpose-built AI infrastructure uniquely designed to combine the latest GPUs and InfiniBand networking. - Automated Machine Learning: Rapidly create accurate machine learning models for tasks including classification, regression, vision, and natural language processing. - Responsible AI: Build responsible AI solutions with interpretability capabilities. Assess model fairness through disparity metrics and mitigate unfairness. - Model Catalog: Discover, fine-tune, and deploy foundation models from Microsoft, OpenAI, Hugging Face, Meta, Cohere, and more using the model catalog. - Prompt Flow: Design, construct, evaluate, and deploy language model workflows with prompt flow. - Managed Endpoints: Operationalize model deployment and scoring, log metrics, and perform safe model rollouts. Primary Value and Solutions Provided: Azure Machine Learning accelerates time to value by streamlining prompt engineering and machine learning model workflows, facilitating faster model development with powerful AI infrastructure. It streamlines operations by enabling reproducible end-to-end pipelines and automating workflows with continuous integration and continuous delivery (CI/CD). The platform ensures confidence in development through unified data and AI governance with built-in security and compliance, allowing compute to run anywhere for hybrid machine learning. Additionally, it promotes responsible AI by providing visibility into models, evaluating language model workflows, and mitigating fairness, biases, and harm with built-in safety systems. ## Azure Machine Learning Pros & Cons **What users like:** - Users find Azure Machine Learning to be **easy to use** , facilitating seamless data management and model implementation. (3 reviews) - Users appreciate the **scalability and integration** of Azure Machine Learning, enhancing AI deployment across various applications. (3 reviews) - Users appreciate the **excellent customer support** of Azure Machine Learning, with helpful documentation and community assistance available. (2 reviews) - Users appreciate the **ease of use and rich features** of Azure Machine Learning for effective data management. (2 reviews) - Users appreciate the **efficiency** of Azure Machine Learning for launching and monitoring jobs seamlessly, enhancing productivity. (2 reviews) - Users appreciate the **implementation ease** of Azure Machine Learning, facilitating quick integration and efficient model training. (2 reviews) - Users value the **scalability and integration** of Azure Machine Learning, enhancing AI deployment and management across applications. (1 reviews) - Users value the **seamless integration with Azure services** that enhances their ability to utilize AI effectively. (1 reviews) - Users appreciate the **automation features** of Azure Machine Learning, simplifying data uploading and pattern recognition. (1 reviews) - Users value the **scalability and integration** of Azure Machine Learning, enabling effortless deployment of AI models across applications. (1 reviews) **What users dislike:** - Users find the **learning curve challenging** , requiring time and effort to navigate the platform's tools effectively. (3 reviews) - Users find Azure Machine Learning's **difficult navigation** frustrating due to its disordered interface and non-intuitive workflows. (2 reviews) - Users find the **user interface disorganized** , leading to confusion and excessive clicking to locate options. (2 reviews) - Users find the **complex interface** of Azure Machine Learning non-intuitive, complicating their workflow and experience. (1 reviews) - Users face a **difficult learning curve** with Azure Machine Learning, especially if they are new to the platform. (1 reviews) - Users find **insufficient learning resources** for Azure Machine Learning, leading to frustrating trial and error experiences. (1 reviews) - Users find Azure Machine Learning **lacking features** , particularly in metric support and job cascading functionality. (1 reviews) - Lack of Guidance (1 reviews) - Limited Customization (1 reviews) - Limited Hours (1 reviews) ## Azure Machine Learning Reviews ### 1. Azure, Powered with AI rich Algorithms made my life simple **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Online Media | Enterprise (> 1000 emp.) **Reviewed Date:** September 11, 2019 **What do you like best about Azure Machine Learning?** Developed a predictive analytics model where I could use data from more than one source. This was pretty hard when i had used a similar platform previously, but in Azure there is a comprehensive package where everything is there ready in a single canvas, where i could just drang and drop. Absolutely zero programming knowledge required, visualization at its best... We all know about Power BI, dont we... 😊 **What do you dislike about Azure Machine Learning?** Not a dislike as it, but storage space is limited to 10 GB **What problems is Azure Machine Learning solving and how is that benefiting you?** Helped in solving a sales analytics problem ### 2. Best platform for learn machine learning and natural language processing(NLP). **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** October 05, 2019 **What do you like best about Azure Machine Learning?** The best part of azure machine learning is that have suitable algorithm for all problem. Best cognitive services like (LUIS) natural language processing free APIs and storage system. All algorithm for data processing. **What do you dislike about Azure Machine Learning?** It is little bit complicated for non coding background learner. **Recommendations to others considering Azure Machine Learning:** Reduce some complication for non coding background learner **What problems is Azure Machine Learning solving and how is that benefiting you?** I build many chatbots for different different client. I used many cognitive services. And it hepl more in NLP. ### 3. Azure ML, rich but not complete **Rating:** 3.5/5.0 stars **Reviewed by:** Reza N. | Technical Lead, Enterprise (> 1000 emp.) **Reviewed Date:** August 21, 2019 **What do you like best about Azure Machine Learning?** Ease of use, the tooling and other MS libs that complement it **What do you dislike about Azure Machine Learning?** Offerings are segregated and building an end-to-end dev cycle is still not straight forward **What problems is Azure Machine Learning solving and how is that benefiting you?** For the moment I still use it like a lab to realize how can our current apps and services benefit from AI ### 4. Machine Learning made incredibly effortless **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Education Management | Mid-Market (51-1000 emp.) **Reviewed Date:** September 02, 2019 **What do you like best about Azure Machine Learning?** I liked the studio which I have been using for sometime now. Its very simple and does a lot of boilerplate stuff without error codes, very smooth. **What do you dislike about Azure Machine Learning?** I would like it cover more state of the art stuff so that we can stay up to date on whats happening new in the ML **What problems is Azure Machine Learning solving and how is that benefiting you?** I work with text processing applications that includes understanding semantic behind text. ### 5. Azure Machine learning review **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** August 15, 2019 **What do you like best about Azure Machine Learning?** How easy is to work with this product. Increase productivity with integrated CI/CD, machine learning pipelines, and model management. **What do you dislike about Azure Machine Learning?** Too many windows and To enable your production scenarios, you may need to use resources beyond the free amounts. **Recommendations to others considering Azure Machine Learning:** Azure products for 12 months, $200 credit to spend for the first 30 days of sign up, and access to more than 25 products that are always free. **What problems is Azure Machine Learning solving and how is that benefiting you?** Identify suitable algorithms and hyper-parameters faster. ### 6. Good, A steep learning curve but worth the payoff **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Building Materials | Mid-Market (51-1000 emp.) **Reviewed Date:** August 31, 2019 **What do you like best about Azure Machine Learning?** The ease of repetitive tasks now means quickly and efficiently what might have taken a few hours or multiple employees can now be done quickly and effortlessly **What do you dislike about Azure Machine Learning?** Like all offerings the complexity means coming into it can be confusing with a steep learning curve. **Recommendations to others considering Azure Machine Learning:** Spend a good amount of time learning the offering in your own environment first **What problems is Azure Machine Learning solving and how is that benefiting you?** Automation and chat bots ### 7. Helpful and a good starting point for anyone looking to start with machine learning models **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** September 09, 2019 **What do you like best about Azure Machine Learning?** The best part of Azure Machine Learning is the support and the ease of use. Easy to implement and the graphical interface is quick to adapt to. **What do you dislike about Azure Machine Learning?** If we compare it to other open source platforms , getting access and effective memory usage . **What problems is Azure Machine Learning solving and how is that benefiting you?** Predicting test responses to a new product to be introduce in the market. ### 8. A powerful tool for machine learning **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** July 06, 2019 **What do you like best about Azure Machine Learning?** it has a very intuitive and friendly environment it makes machine learning easy cause of the drag and drop feature its fast and easy to use **What do you dislike about Azure Machine Learning?** Azure ML has very few machine learning Algorithms i.e it doesn't have most of the tree algorithms. **Recommendations to others considering Azure Machine Learning:** I recommend Azure ML to people who want to start ML and have little experience with coding. **What problems is Azure Machine Learning solving and how is that benefiting you?** We use Azure Ml to build basic machine learning algorithms and to teach staffs with no programming experience ML ### 9. Easy to use and work on **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Education Management | Small-Business (50 or fewer emp.) **Reviewed Date:** March 19, 2019 **What do you like best about Azure Machine Learning?** This software is very to use and work with. The UI for this application is amazing and we can easily create Machine learning methods with the databases on the server. The ease with with the models can be built is amazing. I would recommend this software to all the folks out there. **What do you dislike about Azure Machine Learning?** Still needs improvements in terms of more machine learning models. Adding more models will improve the number of iterations that can be performed on the same data. It will help for the overall success of the project. **Recommendations to others considering Azure Machine Learning:** Its a software hassle free and hence would highly recommend this. **What problems is Azure Machine Learning solving and how is that benefiting you?** For creating models like prediction models and forecasting models by using different Machine Learning methods. So instead of writing the whole codes, just using the Microsoft Azure has helped a lot. ### 10. Easy to implement and to start to work with **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Civic & Social Organization | Enterprise (> 1000 emp.) **Reviewed Date:** August 22, 2019 **What do you like best about Azure Machine Learning?** As my title says, the process when you start to work with the solution is not painful and is easy to start your implementation **What do you dislike about Azure Machine Learning?** I would like to have more training resources **Recommendations to others considering Azure Machine Learning:** More documentation and demos **What problems is Azure Machine Learning solving and how is that benefiting you?** Training models to identify images on video streaming to recognize SLA language ### 11. Open Source, simple and scalable **Rating:** 4.0/5.0 stars **Reviewed by:** sheng t. | Data Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** March 20, 2019 **What do you like best about Azure Machine Learning?** I like that it's transferable and able to take in multiple sources and pretty versatile with other programming languages. It also has remote executions and dedicated pre-trained models to solve problems **What do you dislike about Azure Machine Learning?** I dislike the usability on some libraries and the installation process **What problems is Azure Machine Learning solving and how is that benefiting you?** We provide data analytics solutions to consumers and provide them with models to predict future outcomes ### 12. My opinion regarding Microsoft Machine Learning Server **Rating:** 3.5/5.0 stars **Reviewed by:** Sheetal V. | Project Development Manager, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** January 17, 2019 **What do you like best about Azure Machine Learning?** Microsoft Machine Learning Server is designed with Microsoft R and Python with AI capabilities. It get frequent updates with updated features and AI. It helps to scale large data, to build AI specific intelligent applications. Moreover its available on premises as well on cloud. **What do you dislike about Azure Machine Learning?** It support multiple languages and is open source. But for processing large amount of data you need Microsoft specific set of algorithms like MicrosoftML **What problems is Azure Machine Learning solving and how is that benefiting you?** Microsoft has been used for analysing the database dumps to get specific information. ### 13. Azure ML is fun to use **Rating:** 5.0/5.0 stars **Reviewed by:** Daniel H. | diseño web, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** April 27, 2018 **What do you like best about Azure Machine Learning?** First of all, I must say that its interface is so pleasant to the eye and searching and dragging in the different components into the dashboard is fun. Configuring the modules is very simple, with a lot of features being preconfigured. Visualizing the results is also very neat and being able to publish the service as web API with minimal effort is so cool. **What do you dislike about Azure Machine Learning?** So far, I don't find anything I dislike about Azure Machine Learning, but I must admit that my level of apprentice in this field is at a beginner's level. **Recommendations to others considering Azure Machine Learning:** An intermediate to advanced knowledge of regression models, data sorting and cleansing, is a must, as with other machine learning software. Also comparing the different learning models, one another is definitely necessary to optimize the results. **What problems is Azure Machine Learning solving and how is that benefiting you?** Recently, I was asked to perform some sort of prediction for a drugstore, based on data gathered through a web page survey, in order to rate their customers level of approval, and therefore try to forecast the coming months sales volume. After searching for different options, I found Azure ML and decided to try it out, after a while of going through the help guides and support pages, I started taken my first steps, testing and comparing different regression methods and data transformations, and when I started to get a hang of it, I realize how powerful this tool is. It has such a vast number of resources available, that makes it a must have. ### 14. My experience with this software has been really good. **Rating:** 4.0/5.0 stars **Reviewed by:** Saransh D. | Graduate Research Assistant, Higher Education, Enterprise (> 1000 emp.) **Reviewed Date:** June 12, 2018 **What do you like best about Azure Machine Learning?** Azure Machine Learning platform is aimed at setting a powerful playground both for newcomers and experienced data scientists. It is more more flexible in terms of out-of-the-box algorithms when compared with other platforms. A big part of Azure ML is Cortana Intelligence Gallery. It’s a collection of machine learning solutions provided by the community to be explored and reused by data scientists. It is a powerful tool for starting with machine learning and introducing its capabilities to new employees. On the other hand, Azure ML supports graphical interface to visualize each step within the workflow. Perhaps the main benefit of using Azure is the variety of algorithms available to play with. It supports around 100 methods that address classification (binary+multiclass), anomaly detection, regression, recommendation, and text analysis. It also has one clustering algorithm (K-means). Once can execute the 'R ' scripts within the platform to meet his or her needs. **What do you dislike about Azure Machine Learning?** Going towards machine learning with this platform has some learning curve. It is a it more expensive than the Amazon platform. Sometimes the speed of execution can be slow. **Recommendations to others considering Azure Machine Learning:** It is one of the most user friendly cloud hosting platforms and integrates well with other MIcrosoft products. **What problems is Azure Machine Learning solving and how is that benefiting you?** It has helped me in easy drag-and-drop of objects on the interfaces to create models that can be pushed to the web as services to be utilized by tools like business intelligence systems. ### 15. Experimental POS project on Azure ML - smooth implementation **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** January 17, 2019 **What do you like best about Azure Machine Learning?** Easy to use API implementation, clean API structure **What do you dislike about Azure Machine Learning?** The documentation could be better. Adding high amounts of training data takes time. **Recommendations to others considering Azure Machine Learning:** As a POC product, this was very easy to use and quick to implement. **What problems is Azure Machine Learning solving and how is that benefiting you?** We did a POC on an algorithm based data analytics. Used Azure ML as the ML service where we input our training data and then extract results from actual data. ### 16. Review for Azure Machine Learning Studio **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** September 14, 2018 **What do you like best about Azure Machine Learning?** I like is the ease of integration with R and Python. One can develop machine learning models in any of these and deploy production-ready models to Azure. Azure ML also supports graphical interface to visualize each step within the workflow. **What do you dislike about Azure Machine Learning?** . It is more expensive than the Amazon platform and sometimes the speed of execution can be slow. Also as the support to salesforce is not present. We cannot deploy the API to read and write data from Salesforce **Recommendations to others considering Azure Machine Learning:** It is one of the most user-friendly cloud hosting platforms and integrates well with other Microsoft products. **What problems is Azure Machine Learning solving and how is that benefiting you?** We use it for Computer vision and NLP problems. It is very good for prototyping. I would recommend it. ### 17. Smooth platform train and test your models with visualizing the performance **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Education Management | Small-Business (50 or fewer emp.) **Reviewed Date:** February 08, 2019 **What do you like best about Azure Machine Learning?** Ability to drag and drop the blocks of algorithms and other functions **What do you dislike about Azure Machine Learning?** I feel like a user has less flexibility to operate on his own when certain logic is to be employed. **What problems is Azure Machine Learning solving and how is that benefiting you?** building predictive models ### 18. Good for beginners **Rating:** 4.0/5.0 stars **Reviewed by:** Janish S. | Head Technical Program Manager, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** October 09, 2018 **What do you like best about Azure Machine Learning?** The compatibility that it works for every enterprise, compatibility with existing microsoft products **What do you dislike about Azure Machine Learning?** i would say the speed as compared to amazon web services **What problems is Azure Machine Learning solving and how is that benefiting you?** Trying to reduce dependencies with physical servers, trying to automate processes and increasing speed of transactions. ### 19. Azure is a high quality engine **Rating:** 2.0/5.0 stars **Reviewed by:** Verified User in Management Consulting | Small-Business (50 or fewer emp.) **Reviewed Date:** June 28, 2018 **What do you like best about Azure Machine Learning?** I appreciate the ability for azure to add in dimensionality to processing power. It is extremely power as a PAAS SAAS IAAS platform and allows users to determine on their own the best approach to the solution of their specific individual needs. I also like the quality with which Azure provides customer support and help assistance to clients. It is a robust platform with a robust user base. **What do you dislike about Azure Machine Learning?** I dislike the price point at which Azure markets itself. It does not make sense to charge that much given their lower costs compared to competitors. **What problems is Azure Machine Learning solving and how is that benefiting you?** Business problems such as ML can easily be solved using Azure. Azure provides a way to learn and segment data cleanly. ### 20. Opinion on Azure Machine learning for building models for fitting the data I have worked on. **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Higher Education | Small-Business (50 or fewer emp.) **Reviewed Date:** October 06, 2018 **What do you like best about Azure Machine Learning?** The fast and easy way to build complex predictive models without knowing much of the programming stuff.The organizing of data and being able to run R and python necessary scripts on the data made it a little easier. **What do you dislike about Azure Machine Learning?** The sentiment analysis results were not accurate and the response time on queries is not fast. **What problems is Azure Machine Learning solving and how is that benefiting you?** predictive and statistical analysis for the research data to provide results ### 21. Microsoft review **Rating:** 2.5/5.0 stars **Reviewed by:** Verified User in Marketing and Advertising | Mid-Market (51-1000 emp.) **Reviewed Date:** May 20, 2018 **What do you like best about Azure Machine Learning?** It’s an amazing product with a lot of scope and ways it could improve, this is very good at enabling you to drag and frop without the necessary knowledge of being able to code to the highest level including many packages if you were to custom code **What do you dislike about Azure Machine Learning?** Nothing really as it is a really great product and helps you learn quickly **Recommendations to others considering Azure Machine Learning:** This is a great product that will help you in many ways if you are looking for an easy way to impliment code **What problems is Azure Machine Learning solving and how is that benefiting you?** We are solving the ways in which it helps us run the business on a day to day and benefits us by taking a lot of stress on our hands. This also enables us to code in an easier manner making us manage our time more efficiently ### 22. Azure Machine Learning Studio Review **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** August 25, 2018 **What do you like best about Azure Machine Learning?** It is less restrictive when it comes to tools and is user friendly and experiments for data models can be published quickly. Also has a free version which can be used to learn. **What do you dislike about Azure Machine Learning?** Some components slow. Also there is no version control integration like Git for the graphs obtained in experiments. **What problems is Azure Machine Learning solving and how is that benefiting you?** The biggest benefit is that though with limited features, it has a free version which lets us trial it, learn the platform and if comfortable, purchase it. ### 23. Azure Review **Rating:** 4.5/5.0 stars **Reviewed by:** Lindsay Y. | Laboratory Aide, Hospital & Health Care, Enterprise (> 1000 emp.) **Reviewed Date:** June 06, 2018 **What do you like best about Azure Machine Learning?** This data storage site makes it easy to store large files needed in computer data analyses. **What do you dislike about Azure Machine Learning?** The formatting of the files can be difficult to categorize. **What problems is Azure Machine Learning solving and how is that benefiting you?** Currently working on extensive code to solve problems in data input. ### 24. Have been working with azure ML studio for over a year **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** August 30, 2018 **What do you like best about Azure Machine Learning?** It simplifies complexity for data scientist **What do you dislike about Azure Machine Learning?** It doesn' work with different model saving approaches **What problems is Azure Machine Learning solving and how is that benefiting you?** computer vision and NLP problems. It is very good for prototyping but not really good for productionizing. ### 25. Azure Machine Learning Studio **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Health, Wellness and Fitness | Mid-Market (51-1000 emp.) **Reviewed Date:** January 29, 2018 **What do you like best about Azure Machine Learning?** The best thing that i like is the ease of integration with R and Python. We can develop machine learning models in any of these and deploy production ready models to Azure. **What do you dislike about Azure Machine Learning?** One of the elements that i most dislike is the support to salesforce is not present. We cannot deploy the API to read and write data from salesforce. We need to bring in SQL Server into the mix and then upload the data from Sql Server to salesforce. This just adds additional maintanance layer. **Recommendations to others considering Azure Machine Learning:** This mainly allows easier integration to other platforms. **What problems is Azure Machine Learning solving and how is that benefiting you?** We use Azure machine learning solutions to deploy production ready machine learning algorithms created using R server. Ease of maintenance and deployment helps us to integrate our solutions across different platforms such as salesforce and CRM. ### 26. It’s good but needs some visual changes. **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in Farming | Enterprise (> 1000 emp.) **Reviewed Date:** October 06, 2018 **What do you like best about Azure Machine Learning?** it's easy to deploy and run the models..this is definitely the best part. **What do you dislike about Azure Machine Learning?** Microsoft UI, its more like a microsoft thing than Machine learning stuff. **What problems is Azure Machine Learning solving and how is that benefiting you?** Data modeling to predict the traits. ### 27. Keeping up with modern technology **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Internet | Small-Business (50 or fewer emp.) **Reviewed Date:** June 05, 2018 **What do you like best about Azure Machine Learning?** Azure learning machine is an advanced form of technology that has allowed to crest datasets and view them in an highly organized manner. **What do you dislike about Azure Machine Learning?** The only pitfall to using this form of technology is that it is not the easiest to understand at first. I had to maneuver through the tabular features before I could move forward. **What problems is Azure Machine Learning solving and how is that benefiting you?** The project I most recently used it for was for a political campaign to reach voters. It was an essay way to organize registered voter information and create a dataset that made it easier to see all their information in one place. ### 28. A great AI, code free easy to use solution **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Transportation/Trucking/Railroad | Small-Business (50 or fewer emp.) **Reviewed Date:** June 13, 2018 **What do you like best about Azure Machine Learning?** It literally took minutes for us to deploy and begin the process, the trial we ran helped as well! I am happy with the use case and the rich features it has to offer. **What do you dislike about Azure Machine Learning?** Nothing in specific, I wish we would have done an AI integration sooner. AI can be a scary beast to uncover until you are comfortable with it. **Recommendations to others considering Azure Machine Learning:** Continue to offer cutting edge automation and easy to use products. I would replace every human with a computer if I could! **What problems is Azure Machine Learning solving and how is that benefiting you?** Automation, Elimination of human errors and issues with employee performance ### 29. Good machine learning APIs to get you started easily **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** July 27, 2018 **What do you like best about Azure Machine Learning?** If you wnat to start with Machine learning, the APIs provided make it really easy for you. Even advanced features as well as custom models are well documented and easily created **What do you dislike about Azure Machine Learning?** It is sometimes hard to figure out which API might fit best in your current project, e.g. the handwriting API ist sometimes best to use printed text **What problems is Azure Machine Learning solving and how is that benefiting you?** We use it for analyzing and optimizing text, images and video ### 30. Easy enough to use **Rating:** 3.5/5.0 stars **Reviewed by:** Sebastiano M. | Enterprise (> 1000 emp.) **Reviewed Date:** July 26, 2018 **What do you like best about Azure Machine Learning?** Drag n drop interface and great office 365 integration **What do you dislike about Azure Machine Learning?** Costing structure is difficult to convey to execs and get their buy in **What problems is Azure Machine Learning solving and how is that benefiting you?** Enhance and deploy machine learning API capabilities ### 31. A Balanced product for new bee, than experienced **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** December 05, 2017 **What do you like best about Azure Machine Learning?** 1. its easy it to create a web service and then deploy it to production 2. Web Based clean user interface **What do you dislike about Azure Machine Learning?** Data Shaping/ Data cleaning interface is clunky at the best Trying to upgrade the package from trail gives you no idea about the subscriptions available. Its simply not seemless **Recommendations to others considering Azure Machine Learning:** Be ready to have custom code and get your hands dirty, there is no way out of having your own deep learning cluster in house and on cloud with GPU (if not multi gpu then at least single gpu). TensorFlow has the highest visibility and resource availability in market currently **What problems is Azure Machine Learning solving and how is that benefiting you?** 1. training new staff / or new comers to machine learning 2. getting sample use cases for machine learning run on azure (and forget all the headaches involved in setting up environment) ### 32. Easy to use and excellent software **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Computer & Network Security | Small-Business (50 or fewer emp.) **Reviewed Date:** June 06, 2018 **What do you like best about Azure Machine Learning?** The best feature is the fact it is easy to use and navigate to use the different features **What do you dislike about Azure Machine Learning?** It can seem as there is a limited amount of features **Recommendations to others considering Azure Machine Learning:** Use this software it is easy to use and get used to, you will find most of your duties can be sorted with this software **What problems is Azure Machine Learning solving and how is that benefiting you?** THe fact that 90% of daily duties at work can be used to complete with this software ### 33. Using Microsoft Machine Learning Server for Robotics **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Medical Devices | Small-Business (50 or fewer emp.) **Reviewed Date:** July 18, 2018 **What do you like best about Azure Machine Learning?** Extremely easy to leverage AI technologies without extensive coding experience. **What do you dislike about Azure Machine Learning?** Limited customizability. Internet connectivity a must. **What problems is Azure Machine Learning solving and how is that benefiting you?** Saving R&D costs by using Microsoft's APIs opposed to coding from scratch. ### 34. Brief exposure to Azure ML was enlightening! **Rating:** 4.0/5.0 stars **Reviewed by:** Jake D. | Senior Engineer - Big Data Lead, Automotive, Enterprise (> 1000 emp.) **Reviewed Date:** December 12, 2017 **What do you like best about Azure Machine Learning?** The automated processing of selected algorithms is impressive. **What do you dislike about Azure Machine Learning?** Not much to dislike - I'm very impressed with the studio capabilities. **What problems is Azure Machine Learning solving and how is that benefiting you?** So far I have not had a chance to apply it to a business problem, but that is due to the slowness of our internal processes - not Azure ML. ### 35. Good tool for simple models **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Mid-Market (51-1000 emp.) **Reviewed Date:** June 12, 2018 **What do you like best about Azure Machine Learning?** The ease with which we can build data models is cool.drag and drop functionality makes learning it easy **What do you dislike about Azure Machine Learning?** Its not free unlike a lot of other tools today **What problems is Azure Machine Learning solving and how is that benefiting you?** Makes predictive analytics lot simpler ### 36. Spark, Docker, Cognitive Toolkit, TensorFlow, Caffe - many features supported **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** May 28, 2018 **What do you like best about Azure Machine Learning?** I like Spark functionality - as real time data stream Azure helps in deep machine learning. Serverless, drag and drop development - Studio is awesome. **What do you dislike about Azure Machine Learning?** still evaluating the product , will need to come up soon. **What problems is Azure Machine Learning solving and how is that benefiting you?** POC for internal project. ### 37. azure machine learning- easy yet powerful **Rating:** 5.0/5.0 stars **Reviewed by:** ARUN R. | Small-Business (50 or fewer emp.) **Reviewed Date:** October 31, 2016 **What do you like best about Azure Machine Learning?** it has got a nice user interface, drag and drop components and connect them to build your model. you can also custiomize various components or code in python or R to have a custom component. it has nice interface to visualize data and easy to deploy your project. you can upload dataset from various sources . the best thing is its amazing interface. it also has cortana intelligence suite and other stuff wrth trying. it gets work done fast and easy. it trains the model fast. **What do you dislike about Azure Machine Learning?** you have to have internet connection to use it.interface to code in python and R support is not good . a better interface to write code was expected. to use it, you need to know what you are doing. you need to have skills in data science and machine learning. **Recommendations to others considering Azure Machine Learning:** it is easy to get started with and also comes with nice support . it has got cortana intelligence suite which is also helpful . if you have knowledge of data science and machine learning , it is must to try it once . you can upload dataset from various sources and train a model real quick just on the browser. it has great customization options to be used. it gives nice suggestions while selecting columns from dataset. **What problems is Azure Machine Learning solving and how is that benefiting you?** i use it to create machine learning models with it for training various kinds of dataset available . it helps in creating recommender systems and other models . ### 38. Good for machine learning **Rating:** 3.0/5.0 stars **Reviewed by:** Paloma D. | Technical Analyst, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** August 27, 2017 **What do you like best about Azure Machine Learning?** I like its ability to analyze complex algorithms and come up with great correlations and regressions. **What do you dislike about Azure Machine Learning?** I dislike that it has certain limitations, wish it was more sophisticated **What problems is Azure Machine Learning solving and how is that benefiting you?** It helps with analyzing large datasets and looking for correlations. ### 39. Good tool for users with limited programming experience but not very user friendly **Rating:** 2.5/5.0 stars **Reviewed by:** Isabel O. | Research Analyst, Research, Mid-Market (51-1000 emp.) **Reviewed Date:** December 08, 2016 **What do you like best about Azure Machine Learning?** I like that people that don't have a lot of programming experience in languages like R or Python can use "templates" for running machine learning algorithms. This makes this tool available for non experts in the field. **What do you dislike about Azure Machine Learning?** I dislike that the interface is not very user friendly. It took me a while to figure out how to connect the arrows and how the work flow works. I would like it to be more intuitive. **Recommendations to others considering Azure Machine Learning:** I would recommned it too people with medium programming skills. For people that have enough tools to program wit out I would say there are more benefits of writting your own code. **What problems is Azure Machine Learning solving and how is that benefiting you?** I am using it to run algorithms and test some machine learning models, and comparing them to stadard regression model using other software. ### 40. Azure ML - User friendly high capability **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** October 25, 2017 **What do you like best about Azure Machine Learning?** Azure comes with various connectors for ML and other advanced analytics tasks. **What do you dislike about Azure Machine Learning?** Better user guides and support materials are required **What problems is Azure Machine Learning solving and how is that benefiting you?** We are trying to automate tasks based on subject of email using ML applications. ## Azure Machine Learning Discussions - [What is Azure Machine Learning Studio used for?](https://www.g2.com/discussions/what-is-azure-machine-learning-studio-used-for) - 1 comment - [View Azure Machine Learning pricing details and edition comparison](https://www.g2.com/products/microsoft-azure-machine-learning/reviews?page=2§ion=pricing&secure%5Bexpires_at%5D=2026-07-17+19%3A14%3A47+-0500&secure%5Bsession_id%5D=b0602c23-10aa-4349-85e8-203e9e149ed4&secure%5Btoken%5D=223786ac0b51c4036440306d7e27dfa152475ee9d38e578679e825571f463e41&format=llm_user) ## Azure Machine Learning Features **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **System** - Data Ingestion & Wrangling **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Scalability and Performance - Generative AI Infrastructure** - AI High Availability - AI Model Training Scalability - AI Inference Speed **Prompt Engineering - Large Language Model Operationalization (LLMOps) ** - Prompt Optimization Tools - Template Library **Inference Optimization - Large Language Model Operationalization (LLMOps)** - Batch Processing Support **Data Ingestion & Preparation - Low-Code Machine Learning Platforms** - Automatic Data Profiling & Quality Assessment - Multi‑Source Connector Support - Schema Drift / Change Detection **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Management** - Cataloging - Monitoring - Governing - Model Registry **Model Development** - Feature Engineering **Operations** - Metrics - Infrastructure management - Collaboration **Cost and Efficiency - Generative AI Infrastructure** - AI Cost per API Call - AI Resource Allocation Flexibility - AI Energy Efficiency **Model Garden - Large Language Model Operationalization (LLMOps)** - Model Comparison Dashboard **Model Construction & Automation - Low-Code Machine Learning Platforms** - Guided Algorithm & Hyperparameter Recommendation - Code Extensibility - Automated Feature Engineering **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Management** - Cataloging - Monitoring - Governing **Integration and Extensibility - Generative AI Infrastructure** - AI Multi-cloud Support - AI Data Pipeline Integration - AI API Support and Flexibility **Custom Training - Large Language Model Operationalization (LLMOps)** - Fine-Tuning Interface **Deployment** - Managed Service - Application - Scalability **Generative AI** - AI Text Generation - AI Text Summarization **Security and Compliance - Generative AI Infrastructure** - AI GDPR and Regulatory Compliance - AI Role-based Access Control - AI Data Encryption **Application Development - Large Language Model Operationalization (LLMOps) ** - SDK & API Integrations **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Usability and Support - Generative AI Infrastructure** - AI Documentation Quality - AI Community Activity **Model Deployment - Large Language Model Operationalization (LLMOps) ** - One-Click Deployment - Scalability Management **Guardrails - Large Language Model Operationalization (LLMOps)** - Content Moderation Rules - Policy Compliance Checker **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making **Model Monitoring - Large Language Model Operationalization (LLMOps)** - Drift Detection Alerts - Real-Time Performance Metrics **Security - Large Language Model Operationalization (LLMOps)** - Data Encryption Tools - Access Control Management **Gateways & Routers - Large Language Model Operationalization (LLMOps)** - Request Routing Optimization ## Top Azure Machine Learning Alternatives - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (653 reviews) - [Dataiku](https://www.g2.com/products/dataiku/reviews) - 4.4/5.0 (212 reviews) - [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews) - 4.3/5.0 (53 reviews)