github.com
Tutorial on Python time-series model deployment.
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github.com
Deep learning based facial detector for Python coming with facial landmarks.
spark.apache.org
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. It provides high-level APIs in Java, Scala, Python and R, and supports Spark SQL, pandas API on Spark, MLlib, GraphX and Structured Streaming. The documentation covers downloads, the shell and client applications.
staying.fun
Staying is a code visualization platform for Python, JavaScript and C++. It animates execution flow, traces variables and monitors memory allocation, and offers code optimization suggestions. The documentation collects language support, data-structure examples and runnable code.
greenteapress.com
Green Tea Press is the publisher of free books by Allen B. Downey, including Think Python and Think Bayes. The books are available under free licenses that allow copying, distribution and modification, in several electronic formats, with some also sold in hard copy.
thelmbook.com
The Hundred-Page Language Models Book by Andriy Burkov is a concise hands-on guide covering machine learning basics through advanced transformer architectures and large language models. It explains AI fundamentals, text representation, count-based models, recurrent neural networks, and transformers, with mathematical foundations and Python code examples. The book targets ML practitioners and engineers building text-based applications.
tpointtech.com
Tpoint Tech is a tutorial site offering free online tutorials and interview questions covering Java, Android, JavaScript, SQL, Python, PHP and other technology topics, aimed at beginners and professionals. It states that it provides access to more than 500 tutorials.
docs.ray.io
Tune is a Python library for experiment execution and hyperparameter tuning at any scale. It supports machine learning frameworks including PyTorch, XGBoost, and TensorFlow and Keras, and runs algorithms such as Population Based Training (PBT) and HyperBand/ASHA. It also integrates with hyperparameter optimization tools including Ax, BayesOpt, BOHB, Nevergrad, and Optuna.
centre-for-humanities-computing.github.io
tweetopic is a Python library for topic modelling of Tweets and other short texts. Its documentation site provides an API reference and a usage guide covering installation, the Dirichlet Multinomial Mixture Model, the Biterm Topic Model, pipelines, visualization and model persistence.
browser.engineering
Web Browser Engineering is a book by Pavel Panchekha and Chris Harrelson that explains how web browsers work by building a basic but complete browser, from networking to JavaScript, in a couple thousand lines of Python. It is available from Bookshop, B&N and Amazon, and in Korean and Japanese translations.
wumbo.net
Wumbo is a math reference site for students, teachers, and enthusiasts. It organizes core concepts, worked examples, formulas, functions, a glossary, notation, operators, symbols, and videos, including a video on quaternions implemented in Python. It offers a contributing membership that funds future videos and resources.
github.com
Better DeepSeek is an open-source browser extension that adds tools to the DeepSeek chat interface, including a customizable system prompt, persistent memory, and tag-based output. It can generate downloadable files, PowerPoint and Excel documents, and multi-file ZIP projects, and run Python in the browser. The project is described as unofficial and independent.
coursera.org
Andrew Ng’s Machine Learning at Stanford University is a Coursera course titled 'Supervised Machine Learning: Regression and Classification'. It is the first course of the Machine Learning Specialization. The course teaches how to build machine learning models in Python using NumPy and scikit-learn, covering regression and classification. It is aimed at beginners, requires flexible scheduling over three weeks at ten hours per week, and offers a shareable certificate.
astroml.org
astroML is a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, matplotlib and astropy, distributed under the 3-clause BSD license. It provides statistical and machine learning routines for analyzing astronomical data, loaders for open astronomical datasets, and examples of analyzing and visualizing datasets. The project was started in 2012 to accompany a textbook on statistics, data mining and machine learning in astronomy.
github.com
autoai is an open-source Python framework for automatic artificial intelligence focused on regression and classification tasks over numerical data. It automates model search, hyper-parameter tuning, and generates high-quality Jupyter Notebook code for resulting models.
github.com
AutoViz is a Python library that automatically visualizes any dataset, any size, with a single line of code. It also offers the FixDQ() function for a quick assessment of dataset quality and fixing data quality issues. The project aims to provide an automated approach to exploratory data analysis through quick and easy data visualization plus data quality, abstracting away the complexities of various plotting libraries and techniques.
github.com
BabyCommandAGI is a Python script system based on BabyAGI that is designed to test combining CLI and LLM interfaces, with the thinking part of BabyAGI greatly simplified to execute commands efficiently. The README warns that it may unintentionally destroy the environment, recommends running it in a virtual environment such as Docker, and recommends Claude 3.7 Sonnet or higher.
github.com
BambooAI is an LLM-driven data analyst tool that operates in a persistent Python kernel. It is available as a web app with Docker-isolated execution, supports user-provided model keys, and is compatible with open weights models via provider or local deployment.
pypi.org
Python bindings for the BLLIP natural language parser.
paepper.com
A blog post describing a small library for building agents controlled by large language models, inspired by langchain. The agent is instructed by a prompt and runs in a loop of Thought, Action and Observation. Implemented tools include executing Python code in a REPL, Google search and Hacker News search.
github.com
ChatGPT Prompts for Data Science is a GitHub repository containing 60 useful prompts for data science tasks. It includes prompts for writing Python code, automatic machine learning, and other data science workflows.
github.com
ChefBoost is a lightweight decision tree framework for Python. It supports standard algorithms including ID3, C4.5, CART, CHAID and regression trees, as well as advanced techniques such as gradient boosting, random forest and Adaboost, with support for categorical features.
github.com
Chunk Tuner is a tool that benchmarks chunking strategies for a RAG corpus and recommends a configuration. It benchmarks strategies such as fixed-token windows, recursive character splitting, semantic splitting and PDF structural chunking, scoring each against retrieval metrics. It is available as a Python library, a CLI and an MCP server.
codecademy.com
Codecademy's Data Scientist: Machine Learning Specialist Career Path is a beginner-level course covering Python 3, SQL, pandas, scikit-learn, Matplotlib, and TensorFlow. The path is listed as taking 95 hours on average and includes 59 projects with no prerequisites, and is described as teaching analysis of data, drawing predictions with machine learning, and building neural networks.