Think Stats is an introduction to probability and statistics for Python programmers, emphasizing simple techniques for exploring real data sets and answering questions. It includes case studies using datasets from the National Institutes of Health and other sources, with exercises using short programs. The second edition is no longer current and is available under a Creative Commons license.
Apache Storm is a free and open source distributed realtime computation system. It processes unbounded streams of data and is simple, can be used with any programming language, and integrates with queueing and database technologies. Listed use cases include realtime analytics, online machine learning, continuous computation, distributed RPC and ETL.
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing statistical graphics, and covers relational, distribution, categorical, regression and multi-plot grids, along with figure theming and color palettes.
A personal blog by Alex Smola titled Adventures in Data Land, covering machine learning topics. Entries include efficient LLM inference tutorials, random projections, effective sample size, voice agents and evaluation, and porting MXNet to Blackwell and Apple Silicon. Posts reference events such as the Machine Learning Summer School 2026 in NYC.
Ruffus is an open-source computation pipeline library for Python, used in science and bioinformatics. It is designed to automate scientific and other analyses with a lightweight, standard-Python syntax, and can be installed from the Python Package Index.
Analyzes structured data and helps produce queries, insights or visualizations.
A data visualization by Chris Whong showing the activities of one random NYC yellow taxi on a single day in 2013, including where it operated and how much money it made. It uses taxi trip data provided by the Taxi and Limousine Commission via a FOIL request. Trip routes were produced with Google's Directions API and are not assumed accurate.
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Apache Storm is a free and open source distributed realtime computation system. It processes unbounded streams of data and is simple, can be used with any programming language, and integrates with queueing and database technologies. Listed use cases include realtime analytics, online machine learning, continuous computation, distributed RPC and ETL.
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing statistical graphics, and covers relational, distribution, categorical, regression and multi-plot grids, along with figure theming and color palettes.
A personal blog by Alex Smola titled Adventures in Data Land, covering machine learning topics. Entries include efficient LLM inference tutorials, random projections, effective sample size, voice agents and evaluation, and porting MXNet to Blackwell and Apple Silicon. Posts reference events such as the Machine Learning Summer School 2026 in NYC.
Ruffus is an open-source computation pipeline library for Python, used in science and bioinformatics. It is designed to automate scientific and other analyses with a lightweight, standard-Python syntax, and can be installed from the Python Package Index.
Analyzes structured data and helps produce queries, insights or visualizations.
A data visualization by Chris Whong showing the activities of one random NYC yellow taxi on a single day in 2013, including where it operated and how much money it made. It uses taxi trip data provided by the Taxi and Limousine Commission via a FOIL request. Trip routes were produced with Google's Directions API and are not assumed accurate.
