Data Science & ML Platforms tools

50 tools filed under Data Science & ML Platforms, in 4 categories. Open a profile for verified pricing, features and alternatives.

Latest Data Science & ML Platforms coverage All categories

Data labeling & annotation

Tool	Pricing model	Free tier	Open source
CVAT Open-source, self-hosted tool focused on image and video annotation for computer vision, with bounding boxes, polygons and tracking.	Open source + paid	Yes	Yes
Encord Multimodal data platform covering curation, AI-assisted annotation and model evaluation for vision, video, audio, text and medical imaging.	Quote only	No	No
Label Studio Open-source, self-hosted annotation tool supporting images, text, audio, video and time-series data through a configurable UI.	Open source + paid	Yes	Yes
Labelbox Enterprise annotation and data-curation platform (Annotate, Catalog) that has expanded into RLHF and agent-training data services.	Quote only	Yes	No
Scale AI Large-scale data-labeling and data-engine platform combining tooling, managed human workforces and RLHF services for AI training data.	Usage-based	Yes	No
Snorkel AI Programmatic-labeling platform (Snorkel Flow) that generates training labels from heuristic rules and weak supervision instead of manual annotation.	Quote only	No	No
SuperAnnotate Multimodal annotation and MLOps platform with a customizable editor, data curation and analytics for scaling AI training-data projects.	Quote only	No	No
Surge AI Human-data platform providing an expert labeling workforce and off-the-shelf RL environments for training and evaluating LLMs.	Quote only	No	No
V7 Annotation platform for images, video and documents, strong in medical imaging formats, with AI-assisted and auto-tracking labeling.	Quote only	No	No

Data science & ML platforms

Tool	Pricing model	Free tier	Open source
Altair RapidMiner Visual, drag-and-drop platform for data prep, machine learning, and enterprise AI, now part of Siemens.	Quote only	No	No
Alteryx Drag-and-drop data preparation and analytic automation platform that extends into predictive modeling.	Subscription	No	No
Amazon SageMaker AWS's fully managed service for building, training, and deploying machine learning models at cloud scale.	Usage-based	Yes	No
Anaconda Python/R distribution and package management platform widely used as the base environment for data science work.	Free tier + paid	Yes	No
Azure Machine Learning Microsoft's cloud platform for building, training, and operationalizing machine learning and generative AI models.	Usage-based	Yes	No
C3 AI Enterprise AI platform for building and deploying large-scale predictive and generative AI applications.	Quote only	No	No
Dataiku Collaborative platform spanning data preparation and machine learning, used by both analysts and data scientists.	Quote only	Yes	No
DataRobot Enterprise AutoML and generative AI platform for building, deploying, and governing predictive models.	Quote only	No	No
Domino Data Lab Enterprise MLOps and data science platform for running, governing, and scaling model workflows across teams.	Quote only	No	No
Google Vertex AI Google Cloud's unified platform for AutoML, custom model training, and access to foundation models.	Usage-based	No	No
H2O.ai Open-source machine learning library and framework, paired with commercial enterprise AutoML and MLOps products.	Free tier + paid	Yes	Yes
IBM Watson Studio IBM's collaborative platform for building, training, and deploying machine learning and generative AI models.	Quote only	Yes	No
Iguazio MLOps-focused AI platform for deploying and managing ML and generative AI applications in production.	Quote only	No	No
KNIME Open-source visual workflow platform for data prep, machine learning, and analytics automation.	Free tier + paid	Yes	Yes

MLOps & experiment tracking

Tool	Pricing model	Free tier	Open source
Arize AI Hosted AI observability platform that monitors deployed ML models and LLM applications for drift, quality, and performance issues.	Free tier + paid	Yes	No
BentoML Open-source framework for packaging and serving ML models as production inference APIs, with a paid managed cloud option.	Open source + paid	Yes	Yes
ClearML Open-source experiment tracker that also bundles pipeline orchestration, dataset versioning, and model deployment.	Free tier + paid	Yes	Yes
Comet Hosted experiment-tracking platform that also offers a separate LLM observability product (Opik).	Free tier + paid	Yes	No
DVC Open-source, Git-like version control for datasets, models, and ML pipelines rather than a tracker or monitoring tool.	Open source + paid	Yes	Yes
Evidently AI Open-source and cloud model-monitoring tool that checks deployed ML/LLM systems for drift, data quality, and performance issues.	Free tier + paid	Yes	Yes
Fiddler AI Hosted AI observability and guardrails platform for monitoring deployed ML models and LLM/agent applications.	Usage-based	Yes	No
Kubeflow Open-source, Kubernetes-native toolkit for orchestrating ML pipelines, notebooks, and training jobs.	Open source + paid	Yes	Yes
Metaflow Open-source Python framework for orchestrating data-science and ML workflows from laptop to production.	Open source + paid	Yes	Yes
MLflow Open-source experiment tracker and model lifecycle toolkit, governed by the Linux Foundation.	Open source + paid	Yes	Yes
neptune.ai Experiment tracker built for high-throughput logging of large-scale and foundation-model training runs.	Free tier + paid	Yes	No
Seldon Kubernetes-native model deployment and serving platform for putting trained ML models into production.	Quote only	No	No
Weights & Biases Hosted experiment tracker and AI evaluation platform for logging training runs, metrics, and model lineage.	Free tier + paid	Yes	No
WhyLabs Formerly a hosted AI-observability platform for monitoring model and data drift; the company has since shut down and open-sourced its stack.	Open source + paid	Yes	Yes

Statistical software

Tool	Pricing model	Free tier	Open source
EViews Econometric software for time-series modeling, forecasting, and panel-data analysis, widely used by economists and financial analysts.	Subscription	Yes	No
GraphPad Prism Statistics and graphing software built for biology and clinical research, combining guided hypothesis tests with publication-ready charts.	Subscription	No	No
IBM SPSS Statistics Menu-driven desktop statistics package for hypothesis testing, survey analysis, and predictive modeling, widely used in social-science research.	Subscription	No	No
JMP Interactive statistical discovery software pairing dynamic data visualization with design of experiments, for engineers and scientists.	Quote only	Yes	No
Julia Open-source, high-performance programming language for numerical and scientific computing, used for statistical simulation at near-C speed.	Open source + paid	Yes	Yes
MATLAB Matrix-based numerical computing environment and language for algorithm development, simulation, and applied statistical/engineering analysis.	Subscription	No	No
Minitab Menu-driven statistical software for quality improvement and Six Sigma, combining hypothesis testing, DOE, and control charts.	Subscription	No	No
Origin Desktop data analysis and graphing software combining spreadsheet-style data handling with curve fitting and publication-quality plots.	Subscription	No	No
R Open-source programming language and environment for statistical computing and graphics, the default language of applied statistics education.	Open source + paid	Yes	Yes
SAS Enterprise statistical analysis and advanced-analytics platform used for validated statistics, data mining, and reporting in regulated industries.	Quote only	No	No
SciPy Open-source Python library of numerical algorithms — optimization, integration, statistics, linear algebra — underlying the scientific Python stack.	Open source + paid	Yes	Yes
Stata Command-driven statistical software for regression, panel-data, and survey analysis, widely used in economics, epidemiology, and political science.	Subscription	No	No
statsmodels Open-source Python library for classical statistical modeling, hypothesis testing, and econometrics alongside pandas and scikit-learn.	Open source + paid	Yes	Yes