Best Machine Learning Software

Compare the Top Machine Learning Software as of October 2025

What is Machine Learning Software?

Machine learning software enables developers and data scientists to build, train, and deploy models that can learn from data and make predictions or decisions without being explicitly programmed. These tools provide frameworks and algorithms for tasks such as classification, regression, clustering, and natural language processing. They often come with features like data preprocessing, model evaluation, and hyperparameter tuning, which help optimize the performance of machine learning models. With the ability to analyze large datasets and uncover patterns, machine learning software is widely used in industries like healthcare, finance, marketing, and autonomous systems. Overall, this software empowers organizations to leverage data for smarter decision-making and automation. Compare and read user reviews of the best Machine Learning software currently available using the table below. This list is updated regularly.

  • 1
    Amazon CodeGuru
    Amazon CodeGuru is a developer tool powered by machine learning that provides intelligent recommendations for improving code quality and identifying an application’s most expensive lines of code. Integrate Amazon CodeGuru into your existing software development workflow where you will experience built-in code reviews to detect and optimize the expensive lines of code to reduce costs. Amazon CodeGuru Profiler helps developers find an application’s most expensive lines of code along with specific visualizations and recommendations on how to improve code to save money. Amazon CodeGuru Reviewer uses machine learning to identify critical issues and hard-to-find bugs during application development to improve code quality.
  • 2
    Giskard

    Giskard

    Giskard

    Giskard provides interfaces for AI & Business teams to evaluate and test ML models through automated tests and collaborative feedback from all stakeholders. Giskard speeds up teamwork to validate ML models and gives you peace of mind to eliminate risks of regression, drift, and bias before deploying ML models to production.
    Starting Price: $0
  • 3
    Keepsake

    Keepsake

    Replicate

    Keepsake is an open-source Python library designed to provide version control for machine learning experiments and models. It enables users to automatically track code, hyperparameters, training data, model weights, metrics, and Python dependencies, ensuring that all aspects of the machine learning workflow are recorded and reproducible. Keepsake integrates seamlessly with existing workflows by requiring minimal code additions, allowing users to continue training as usual while Keepsake saves code and weights to Amazon S3 or Google Cloud Storage. This facilitates the retrieval of code and weights from any checkpoint, aiding in re-training or model deployment. Keepsake supports various machine learning frameworks, including TensorFlow, PyTorch, scikit-learn, and XGBoost, by saving files and dictionaries in a straightforward manner. It also offers features such as experiment comparison, enabling users to analyze differences in parameters, metrics, and dependencies across experiments.
    Starting Price: Free
  • 4
    Synerise

    Synerise

    Synerise

    Synerise is an AI-driven Customer Data & Experience Platform (CDXP). Comprehensive, data-driven solution that centralizes and utilizes customer data to enhance marketing and engagement. Leveraging advanced artificial intelligence, Synerise aggregates data from various sources, creating detailed, real-time customer profiles. Key Strengths of Synerise Synerise excels in several key areas that set it apart from other platforms: - Real-time capabilities. Powered by TerrariumDB, our proprietary database engine designed specifically for behavioural intelligence, real-time computing - AI Engine. The quality of AI algorithms confirmed by successful participation in: Rakuten Data Challenge 2020; Twitter RecSys AI Challenge 2021; KDD Cup 2021; Booking.com AI Challenge 2021 - Time-To-Market. Confirmed by numerous successful implementations across various clients from various industries.
  • 5
    Interplay

    Interplay

    Iterate.ai

    Interplay Platform is a patented low-code platform with 475 pre-built connectors (enterprise, AI, IoT, Startup Technologies). It's used as middleware and as a rapid app building platform by big companies like Circle K, Ulta Beauty, and many others. As middleware, it operates Pay-by-Plate (frictionless payments at the gas pump) in Europe, Weapons Detection (to predict robberies), AI-based Chat, online personalization tools, low price guarantee tools, computer vision applications such as damage estimation, and much more. It also helps companies to go to market with their digital solutions 10X to 17X faster than in old ways.
  • 6
    Obviously AI

    Obviously AI

    Obviously AI

    The entire process of building machine learning algorithms and predicting outcomes, packed in one single click. Not all data is built to be ready for ML, use the Data Dialog to seamlessly shape your dataset without wrangling your files. Share your prediction reports with your team or make them public. Allow anyone to start making predictions on your model. Bring dynamic ML predictions into your own app using our low-code API. Predict willingness to pay, score leads and much more in real-time. Obviously AI puts the world’s most cutting-edge algorithms in your hands, without compromising on performance. Forecast revenue, optimize supply chain, personalize marketing. You can now know what happens next. Add a CSV file OR integrate with your favorite data sources in minutes. Pick your prediction column from a dropdown, we'll auto build the AI. Beautifully visualize predicted results, top drivers and simulate "what-if" scenarios.
    Starting Price: $75 per month
  • 7
    Krista

    Krista

    Krista

    Krista is a nothing-like-code intelligent automation platform that orchestrates your people, apps, and AI so you can optimize business outcomes. Krista builds and integrates machine learning and apps more simply than you can imagine. Krista is purpose-built to automate business outcomes, not just back-office tasks. Optimizing outcomes requires spanning departments of people & apps, deploying AI/ML for autonomous decision-making, leveraging your existing task automation, and enabling constant change. By digitizing complete processes, Krista delivers organization-wide, bottom-line impact.Krista empowers your people to create and modify automations without programming. Democratizing automation increases business speed and keeps you from waiting in the dreaded IT backlog. Krista dramatically reduces TCO compared to your current automation platform.
  • 8
    UnionML

    UnionML

    Union

    Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. ‍ Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior.
  • 9
    Apache Mahout

    Apache Mahout

    Apache Software Foundation

    Apache Mahout is a powerful, scalable, and versatile machine learning library designed for distributed data processing. It offers a comprehensive set of algorithms for various tasks, including classification, clustering, recommendation, and pattern mining. Built on top of the Apache Hadoop ecosystem, Mahout leverages MapReduce and Spark to enable data processing on large-scale datasets. Apache Mahout(TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end or can be extended to other distributed backends. Matrix computations are a fundamental part of many scientific and engineering applications, including machine learning, computer vision, and data analysis. Apache Mahout is designed to handle large-scale data processing by leveraging the power of Hadoop and Spark.
  • 10
    Core ML

    Core ML

    Apple

    Core ML applies a machine learning algorithm to a set of training data to create a model. You use a model to make predictions based on new input data. Models can accomplish a wide variety of tasks that would be difficult or impractical to write in code. For example, you can train a model to categorize photos or detect specific objects within a photo directly from its pixels. After you create the model, integrate it in your app and deploy it on the user’s device. Your app uses Core ML APIs and user data to make predictions and to train or fine-tune the model. You can build and train a model with the Create ML app bundled with Xcode. Models trained using Create ML are in the Core ML model format and are ready to use in your app. Alternatively, you can use a wide variety of other machine learning libraries and then use Core ML Tools to convert the model into the Core ML format. Once a model is on a user’s device, you can use Core ML to retrain or fine-tune it on-device.
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