Data-science Libraries

Boltons is tested against Python 3.7-3.12, as well as PyPy3. Boltons can be added to a project in a few ways. There's the obvious one:

© 2016 - current, Randal S. Olson This is a repository of teaching materials, code, and data for my data analysis and machine learning projects. Be sure to check the documentation (usually in IPython…

This repo contains a curated list of Python tutorials for Data Science, NLP and Machine Learning.

Feast allows ML platform teams to: The list below contains the functionality that contributors are planning to develop for Feast. We welcome contribution to all items in the roadmap! Feast is a commu…

Sebastian Raschka 2014-2024 To install mlxtend, just execute If you use conda, to install mlxtend just execute The mlxtend version on PyPI may always be one step behind; you can install the latest de…

Now let's run the model on the dataset in a streaming fashion. We sequentially interleave predictions and model updates. Meanwhile, we update a performance metric to see how well the model is doing. …

Aim is an open-source, self-hosted ML experiment tracking tool designed to handle 10,000s of training runs. Aim provides a performant and beautiful UI for exploring and comparing training runs. Addit…

There are many ways to get involved in Flyte, including: Flyte is available under the Apache License 2.0. Use it wisely.

Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Flexible integration for any Python script: Build …

Welcome to the Azure Machine Learning Python SDK notebooks repository! Install additional packages as needed: This repository is a push-only mirror. Pull requests are ignored.

Basic usage is as follows:

Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON…

A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and become less lazy. GitHub has problem rendering Jupyter notebook so …

TensorWatch is a debugging and visualization tool designed for data science, deep learning and reinforcement learning from Microsoft Research. It works in Jupyter Notebook to show real-time visualiza…

A simple YAML API to get started quickly, a powerful Python API for total flexibility. Automatically cache your pipeline’s previous results and only re-compute tasks that have changed since your last…

The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on you…

A maintained and curated list of practical and awesome responsible machine learning resources. This section is for responsible ML guidance put forward by organizations or individuals, not for officia…

Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling you to thoroughly test your data and models from research to production. Deepchecks includes: For …

xLearn is developed by high-performance C++ code with careful design and optimizations. Our system is designed to maximize CPU and memory utilization, provide cache-aware computation, and support loc…

You can start with this article that I wrote in Heartbeat magazine (on Medium platform): Jupyter notebooks covering a wide range of functions and operations on the topics of NumPy, Pandans, Seaborn, …

Lance is a modern columnar data format that is optimized for ML workflows and datasets. Lance is perfect for: The key features of Lance include: Download the sift1m subset Convert it to Lance Build …

There are eight subjects in the curriculum, organized into four subject areas. See the "Machine Learning House" section below for detail on why these are the essential foundational subject areas: Lat…

Pandas

Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can…

A trove of carefully curated resources and links (on the topics of software, platforms, language, techniques, etc.) related to data science, all in one place. Homework 3

ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. It provides support for the following machine learning frameworks and packages: License is MI…

This is a continuously updated repository that documents personal journey on learning data science, machine learning related topics. Curated notes on deep learning. Notes related to advertising domai…

A collection of easy Python small projects to help you improve your programming skills. As a Python newbie, I understand the problems that people face when they first begin studying and attempting to…