Best Free Machine Learning Software - Page 4
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Compare the Top Free Machine Learning Software as of August 2026 - Page 4
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Mobius Labs
Mobius Labs
We make it easy to add superhuman computer vision to your applications, devices and processes to give you unassailable competitive advantage. No code, customizable & on-premise AI solutions. -
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IBM Watson OpenScale is an enterprise-scale environment for AI-powered applications that provides businesses with visibility into how AI is created and used, and how ROI is delivered. IBM Watson OpenScale is an enterprise-scale environment for AI-powered applications that provides companies with visibility into how AI is created and used, and how ROI is delivered at the business level. Create and develop trusted AI using the IDE of your choice and power your business and support teams with data insights into how AI affects business results. Capture payload data and deployment output to monitor the ongoing health of business applications through operations dashboards, alerts, and access to open data warehouse for custom reporting. Automatically detects when artificial intelligence systems deliver the wrong results at run time, based on business-determined fairness attributes. Mitigate bias through smart recommendations of new data for new model training.
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Seldon
Seldon Technologies
Deploy machine learning models at scale with more accuracy. Turn R&D into ROI with more models into production at scale, faster, with increased accuracy. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Deploy reduces the time to production by providing production grade inference servers optimized for popular ML framework or custom language wrappers to fit your use cases. Seldon Core Enterprise provides access to cutting-edge, globally tested and trusted open source MLOps software with the reassurance of enterprise-level support. Seldon Core Enterprise is for organizations requiring: - Coverage across any number of ML models deployed plus unlimited users - Additional assurances for models in staging and production - Confidence that their ML model deployments are supported and protected. -
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Aporia
Aporia
Create customized monitors for your machine learning models with our magically-simple monitor builder, and get alerts for issues like concept drift, model performance degradation, bias and more. Aporia integrates seamlessly with any ML infrastructure. Whether it’s a FastAPI server on top of Kubernetes, an open-source deployment tool like MLFlow or a machine learning platform like AWS Sagemaker. Zoom into specific data segments to track model behavior. Identify unexpected bias, underperformance, drifting features and data integrity issues. When there are issues with your ML models in production, you want to have the right tools to get to the root cause as quickly as possible. Go beyond model monitoring with our investigation toolbox to take a deep dive into model performance, data segments, data stats or distribution. -
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Launchable
Launchable
You can have the best developers in the world, but every test is making them slower. 80% of your software tests are pointless. The problem is you don't know which 80%. We find the right 20% using your data so that you can ship faster. We have shrink-wrapped predictive test selection, a machine learning-based approach being used at companies like Facebook so that it can be used by any company. We support multiple languages, test runners, and CI systems. Just bring Git to the table. Launchable uses machine learning to analyze your test failures and source code. It doesn't rely on code syntax analysis. This means it's trivial for Launchable to add support for almost any file-based programming language. It also means we can scale across teams and projects with different languages and tools. Out of the box, we currently support Python, Ruby, Java, JavaScript, Go, C, and C++, and we regularly add support for new languages. -
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Edge Impulse
Edge Impulse
Build advanced embedded machine learning applications without a PhD. Collect sensor, audio, or camera data directly from devices, files, or cloud integrations to build custom datasets. Leverage automatic labeling tools from object detection to audio segmentation. Set up and run reusable scripted operations that transform your input data on large sets of data in parallel by using our cloud infrastructure. Integrate custom data sources, CI/CD tools, and deployment pipelines with open APIs. Accelerate custom ML pipeline development with ready-to-use DSP and ML algorithms. Make hardware decisions based on device performance and flash/RAM every step of the way. Customize DSP feature extraction algorithms and create custom machine learning models with Keras APIs. Fine-tune your production model with visualized insights on datasets, model performance, and memory. Find the perfect balance between DSP configuration and model architecture, all budgeted against memory and latency constraints. -
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MLReef
MLReef
MLReef enables domain experts and data scientists to securely collaborate via a hybrid of pro-code & no-code development approaches. 75% increase in productivity due to distributed workloads. This enables teams to complete more ML projects faster. Domain experts and data scientists collaborate on the same platform reducing 100% of unnecessary communication ping-pong. MLReef works on your premises and uniquely enables 100% reproducibility and continuity. Rebuild all work at any time. You can use already well-known and established git repositories to create explorable, interoperable, and versioned AI modules. AI Modules created by your data scientists become drag-and-drop elements. These are adjustable by parameters, versioned, interoperable, and explorable within your entire organization. Data handling often requires expert knowledge that a single data scientist often lacks. MLReef enables your field experts to relieve your data processing task, reducing complexities. -
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Deeploy
Deeploy
Deeploy helps you to stay in control of your ML models. Easily deploy your models on our responsible AI platform, without compromising on transparency, control, and compliance. Nowadays, transparency, explainability, and security of AI models is more important than ever. Having a safe and secure environment to deploy your models enables you to continuously monitor your model performance with confidence and responsibility. Over the years, we experienced the importance of human involvement with machine learning. Only when machine learning systems are explainable and accountable, experts and consumers can provide feedback to these systems, overrule decisions when necessary and grow their trust. That’s why we created Deeploy. -
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Chalk
Chalk
Powerful data engineering workflows, without the infrastructure headaches. Complex streaming, scheduling, and data backfill pipelines, are all defined in simple, composable Python. Make ETL a thing of the past, fetch all of your data in real-time, no matter how complex. Incorporate deep learning and LLMs into decisions alongside structured business data. Make better predictions with fresher data, don’t pay vendors to pre-fetch data you don’t use, and query data just in time for online predictions. Experiment in Jupyter, then deploy to production. Prevent train-serve skew and create new data workflows in milliseconds. Instantly monitor all of your data workflows in real-time; track usage, and data quality effortlessly. Know everything you computed and data replay anything. Integrate with the tools you already use and deploy to your own infrastructure. Decide and enforce withdrawal limits with custom hold times.Starting Price: Free -
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Pathway
Pathway
Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Pathway comes with an easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: you can use it in both development and production environments, handling both batch and streaming data effectively. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a scalable Rust engine based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with Docker and Kubernetes. -
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Almeta ML
Almeta Cloud
Almeta ML is the easiest way to run machine learning calculations on your website. Calculate propensity to purchase or churn, product recommendations, best time to contact and other metrics for your users. Run a promotion, retarget with ads, make a customized offer, send a campaign. Use with Google Ads, Facebook Ads, Bing Ads or any other advertising network. Get insights into user behavior to enable ML-driven scoring, targeting and personalization. Run pre-built or custom models. Use ML insights, scores and metrics to maximize ROAS and minimize churn. Almeta ML offers usage-based pricing with a free tier. You pay only for what you use, depending on how many events you want to track and how many model calculations you want to run.Starting Price: $0 -
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Orange
University of Ljubljana
Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight! When teaching data mining, we like to illustrate rather than only explain. And Orange is great at that. -
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Analance
Ducen
Combining Data Science, Business Intelligence, and Data Management Capabilities in One Integrated, Self-Serve Platform. Analance is a robust, salable end-to-end platform that combines Data Science, Advanced Analytics, Business Intelligence, and Data Management into one integrated self-serve platform. It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance. -
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Databricks
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
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Vanillatech Labs
Vanillatech
We developed a neuro-bio inspired generic deep learning algorithm that works as simple as an intelligence test. It automatically detects and predicts patterns and allows you to build intelligent apps easily. Our software is easy to use because it offers a straightforward and well defined REST api which allows you to build intelligent apps from any environment. This way you can connect e.g. JavaScript applications, spreadsheets or even your online broker. Our service is free to use for development and testing purposes. Our community edition is open source licensed under SSPL. Vanillatech ML Workstation is the ready-to-use software which runs on your local machine. If you require adaptions or support please contact us for an individual offer. -
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Azure Notebooks
Microsoft
Develop and run code from anywhere with Jupyter notebooks on Azure. Get started for free. Get a better experience with a free Azure Subscription. Perfect for data scientists, developers, students, or anyone. Develop and run code in your browser regardless of industry or skillset. Supporting more languages than any other platform including Python 2, Python 3, R, and F#. Created by Microsoft Azure: Always accessible, always available from any browser, anywhere in the world. -
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Kaggle
Google
Kaggle is a global AI and machine learning platform that brings together developers, researchers, organizations, and data science enthusiasts to build, evaluate, and improve artificial intelligence technologies. The platform offers access to AI competitions, benchmarks, hackathons, datasets, notebooks, pre-trained models, and educational courses that help users develop real-world machine learning skills. Kaggle enables organizations and researchers to host competitions, crowdsource evaluations, publish benchmarks, and discover top AI talent through its large global community of over 31 million users. Users can access free GPU and TPU-powered notebook environments, collaborate on public datasets, explore pre-trained AI models, and participate in large-scale AI research initiatives. The platform also provides learning resources including hands-on courses, solution write-ups, and reproducible notebooks that support both beginners and advanced machine learning practitioners. -
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Sixgill Sense
Sixgill
Every step of the machine learning and computer vision workflow is made simple and fast within one no-code platform. Sense allows anyone to build and deploy AI IoT solutions to any cloud, the edge or on-premise. Learn how Sense provides simplicity, consistency and transparency to AI/ML teams with enough power and depth for ML engineers yet easy enough to use for subject matter experts. Sense Data Annotation optimizes the success of your machine learning models with the fastest, easiest way to label video and image data for high-quality training dataset creation. The Sense platform offers one-touch labeling integration for continuous machine learning at the edge for simplified management of all your AI solutions. -
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Innotescus
Innotescus
Innotescus is a collaborative video and image annotation platform built to streamline Computer Vision development processes via seamless data handling, smart annotation tools, and intuitive collaboration features. Additionally, its data visualization tools and cross-functional collaboration features identify data bias early, improve data accuracy, and enable faster, cost-efficient deployment of high performance Artificial Intelligence. -
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Butler
Butler
Butler is a platform that helps developers turn AI into easy to use APIs. Create, train, and deploy AI Models in minutes. No AI experience required. Use Butler’s easy-to-use user interface to build a comprehensive labeled data set. Forget about painful labeling exercises. Butler automatically chooses and trains the correct ML model for your use case. No need to spend hours analyzing which models perform the best. With a library of features to customize, Butler enables you to tune your model to your exact requirements. Stop spending time wrestling with rigid predefined models or building homegrown custom solutions. Parse key data fields and tables from any unstructured document or image. Free your users from manual data entry with lightning fast document parsing APIs. Extract information from free form text like names, places, terms and any other custom data. Make your product understand your users the same way you do. -
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Craft AI
Craft AI
Our comprehensive proprietary software suite easily integrates into your work streams. Our mission is to make the use of artificial intelligence more accessible to all businesses to ethically and responsibly address their practical needs in record time. Our industry experts will help you define a 15 weeks action plan to build an AI application that meets your challenges. -
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KitOps
KitOps
KitOps is a packaging, versioning, and sharing system for AI/ML projects that uses open standards so it works with the AI/ML, development, and DevOps tools you are already using, and can be stored in your enterprise container registry. It's AI/ML platform engineering teams' preferred solution for securely packaging and versioning assets. KitOps creates a ModelKit for your AI/ML project which includes everything you need to reproduce it locally or deploy it into production. You can even selectively unpack a ModelKit so different team members can save time and storage space by only grabbing what they need for a task. Because ModelKits are immutable, signable, and live in your existing container registry they're easy for organizations to track, control, and audit.