List of data science software

This is a list of data science software and platforms used in data science, which includes programming languages, programming environments, machine learning frameworks, data engineering tools, statistical software, data analysis, plotting, MLOps systems, and more.

These interactive notebooks, IDEs, and platforms provide specialised development environments.

• Apache Zeppelin^[5]
• Architect — Eclipse
• CoCalc
• Dataiku Data Science Studio
• FreeMat
• GNU Octave
• Google Colab
• DataSpell
• Jupyter Notebook / JupyterLab
• Kaggle Notebooks
• MATLAB
• O-Matrix
• PyCharm
• RStudio
• SAS and SAS Studio^[6]
• Spyder
• Visual Studio Code^[7]

The Machine learning / deep learning tools support development in those fields.

Examples of Data engineering tools.

• Apache Airflow
• Apache Flink
• Apache Hadoop
• Apache Kafka
• Apache NiFi
• Apache Spark
• Dask
• Data build tool (dbt)

Examples of Data mining tools.

Data warehouse environments include:

• Amazon Redshift
• Snowflake
• Google BigQuery
• Microsoft Azure Synapse
• Teradata
• Vertica^[10]

Data lake environments include:

• Apache Hadoop
• Cloudera
• Databricks
• Delta Lake
• Amazon S3
• Google Cloud Storage
• Azure Data Lake

• Apriori algorithm – frequent itemset mining and association rule learning in market basket analysis
• Backpropagation – algorithm for training artificial neural networks using gradient descent
• Decision Trees – tree-based algorithm for classification and regression
• Expectation–maximization algorithm – iterative procedure for maximum likelihood estimation with latent variables
• Gradient descent – iterative optimization algorithm for minimizing a loss function
• ID3 algorithm – used to generate a decision tree from a dataset
• K-Means – clustering algorithm based on minimizing within-cluster distances
• K-Nearest Neighbors (KNN) – instance-based learning and classification method
• Linear regression – estimation method for predicting a dependent variable based on independent variables
• Logistic regression – classification algorithm for predicting a binary outcome
• Naive Bayes – probabilistic classifier based on Bayes' theorem
• Ordinary least squares – estimation method for parameters in linear regression
• PageRank – graph-based algorithm for link analysis and search ranking
• Principal component analysis – technique to reduce high-dimensional data while preserving variance
• Q-learning – reinforcement learning algorithm for learning optimal actions
• Random forest – ensemble of decision trees for improved classification or regression
• Sequential minimal optimization – solver for training support vector machines
• Stochastic gradient descent – randomized variant of gradient descent for large-scale machine learning
• Support Vector Machines (SVM) – algorithm for finding a hyperplane to separate classes^[11][12]

• CSPro
• Dataplot
• Epi Map
• X-13ARIMA-SEATS

• BV4.1
• MINUIT
• WinBUGS
• Winpepi

Tools for Data processing and analysis:

Software for Data visualization:

Software for plotting data to support processing and visualise resuls.

• ArcGIS
• Carto
• Epi Map
• GeoDA
• Google Earth Engine
• Leaflet
• Mapbox
• MountainsMap
• QGIS

MLOps and model deployment:

• BentoML^[15]
• Data Version Control (DVC)
• Kubeflow
• MLflow^[16][17]
• Seldon Core^[18]
• Streamlit^[19][20]
• TensorFlow Serving^[21][22]
• Weights & Biases^[23]

• Kaggle – platform for data science competitions, datasets,^[24] and notebooks.
• OpenML – collaborative platform for sharing datasets, algorithms, and experiments.^[25]
• University of California, Irvine Machine Learning Repository^[26]
• Zenodo – open-access repository supported by CERN and the EU.

• Kaggle – online platform for data science education, competitions, datasets, and collaborative learning.
• KNIME – open-source data analytics platform used for teaching data science, machine learning, and workflow-based analysis.
• RapidMiner – used in academic research and education for data mining and machine learning.
• Statistics Online Computational Resource (SOCR) – online tools and instructional resources for statistics education.
• Tanagra (machine learning) – data mining software developed for research and teaching purposes.
• TinkerPlots – explore and analyze data through visual modeling.

Wikibooks has a book on the topic of: Data Science: An Introduction

• Business intelligence software
• List of data science journals
• List of R software and tools
• Lists of mathematical software and List of open-source software for mathematics
• List of numerical-analysis software and List of numerical analysis topics
• List of open-source data science software
• Common Crawl – nonprofit that crawls the web and freely provides its archives and datasets to the public under an MIT License

• 20 Tools for Data Scientists | Pragmatic Institute
• igorbarinov/awesome-data-engineering

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