Data-science Libraries

286 Components & Libraries

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Data-science Libraries

Apache Superset is a Data Visualization and Data Exploration Platform

A modern, enterprise-ready business intelligence web application. Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intellige…

scikit-learn: machine learning in Python

It is currently maintained by a team of volunteers. scikit-learn requires: You can check the latest sources with the command: The project is currently maintained by a team of volunteers.

Learn how to responsibly develop, deploy and maintain production machine learning applications.

Learn the foundations of machine learning through intuitive explanations, clean code and visualizations. Learn how to combine machine learning with software engineering to build production-grade appl…

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

It just takes a few lines of Python to create a beautiful demo like the one above, so let's get started 💫 You can run Gradio in your favorite code editor, Jupyter notebook, Google Colab, or anywhere …

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

After some recent success of Bayesian methods in machine-learning competitions, I decided to investigate the subject again. Even with my mathematical background, it took me three straight-days of rea…

Data Apps & Dashboards for Python. No JavaScript Required.

With Dash Open Source, Dash apps run on your local laptop or workstation, but cannot be easily accessed by others in your organization. Scale up with Dash Enterprise when your Dash app is ready for d…

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

To install the current release: Participating discussions via the following IM groups is also welcomed. Over the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull req…

The "Python Machine Learning (1st edition)" book code repository and info resource

What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into…

An open-source NLP research library, built on PyTorch.

An Apache 2.0 NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks. When you're ready to start your project, we…

An orchestration platform for the development, production, and observation of data assets.

With Dagster, you declare—as Python functions—the data assets that you want to build. Dagster then helps you run your functions at the right time and keep your assets up-to-date. Here is an example o…

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

We start with a high level overview of some foundational concepts in numerical linear algebra. We will use the newsgroups dataset to try to identify the topics of different posts. We use a term-docu…

Low-code framework for building custom LLMs, neural networks, and other AI models

Key features: Install from PyPi. Be aware that Ludwig requires Python 3.8+. Or install with all optional dependencies: Let's fine-tune a pretrained LLaMA-2-7b large language model to follow instructi…

Modin: Scale your Pandas workflows by changing a single line of code

By simply replacing the import statement, Modin offers users effortless speed and scale for their pandas workflows: If you want to install Modin with a specific engine, we recommend: Modin automatica…

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get…

Open Machine Learning Course

mlcourse.ai is still in self-paced mode but we offer you Bonus Assignments with solutions for a contribution of $17/month. The idea is that you pay for ~1-5 months while studying the course materials…

PandasAI is a Python library that integrates generative artificial intelligence capabilities into pandas, making dataframes conversational

Try out PandasAI in your browser: PandasAI is designed to be used in conjunction with pandas. It makes pandas conversational, allowing you to ask questions to your data in natural language. For examp…

An open-source, low-code machine learning library in Python

PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the ex…

:shell: Python-powered, cross-platform, Unix-gazing shell.

Install xonsh from pip: The xonsh shell is developed by a community of volunteers. There are a few ways to help out: We welcome new contributors!

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Get started with W&B in four steps: That's it! Navigate to the W&B App to view a dashboard of your first W&B Experiment. Use the W&B App to compare multiple experiments in a unified…

A collection of machine learning examples and tutorials.

A collection of machine learning examples and tutorials. Please note that not all code from all courses will be found in this repository. Some newer code examples (e.g. most of Tensorflow 2.0) were d…

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Install CatBoost by following the guide for the Next you may want to investigate: If you cannot open documentation in your browser try adding yastatic.net and yastat.net to the list of allowed domain…

:rocket: Build and manage real-life ML, AI, and data science projects with ease!

There are several ways to get in touch with us:

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

cleanlab is: cleanlab supports Linux, macOS, and Windows and runs on Python 3.7+. cleanlab can find label issues from any model's predicted class probabilities if you can produce them yourself. This …

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

published September 20th, 2017 Oh, there are so many things that we improved or added; where should I start!? The one issue on top of my priority list was to fix all the nasty typos that were introdu…

An open source python library for automated feature engineering

Install with pip You can install add-ons individually or all at once by running Below is an example of using Deep Feature Synthesis (DFS) to perform automated feature engineering. In this example, we…

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

imbalanced-learn requires the following dependencies: Additionally, imbalanced-learn requires the following optional dependencies: The examples will requires the following additional dependencies: im…

Related tags

tensorflow-examples

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