The Best 543 Machine learning Libraries

543 Components & Libraries

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Machine learning Repositories

An Open Source Machine Learning Framework for Everyone

TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neura…

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow These models can be applied on: Here are a few examples: In Natural Language Processing: In Computer Vision: In Audio: In Multimoda…

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.

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Travel with us around the world as we apply these classic techniques to data from many areas of the world. Each lesson includes pre- and post-lesson quizzes, written instructions to complete the less…

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…

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Use any of the following services. Next, run the following commands: Finally, start Jupyter: I recommend Python 3.7. If you follow the installation instructions above, that's the version you will get…

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Use any of the following services (I recommended Colab or Kaggle, since they offer free GPUs and TPUs). Next, run the following commands: Finally, start Jupyter: I recommend Python 3.8. If you follow…

Full reference of LinkedIn answers 2023 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

In regression problems we do real value predictions. Basically we try to draw a line/plane/n-dimensional plane along the training examples. In classification problems we split input examples by certa…

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient with the following advantages: Next you may want to read: Documentat…

Create UIs for your machine learning model in Python in 3 minutes

Gradio is an open-source Python library that is used to build machine learning and data science demos and web applications. With Gradio, you can quickly create a beautiful user interface around your …

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

ChatterBot is a machine-learning based conversational dialog engine build in Python which makes it possible to generate responses based on collections of known conversations. The language independent…

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

Contributions are encouraged and always welcome! If you like to add or update projects, choose one of the following ways:

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…

500 AI Machine learning Deep learning Computer vision NLP Projects with code

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…

A toolkit for making real world machine learning and data analysis applications in C++

Go into the examples folder and type: That will build all the examples. If you have a CPU that supports AVX instructions then turn them on like this: Doing so will make some things run faster. Finall…

Launched in 2018. It's 2023 and PySimpleGUI is actively developed & supported. Create complex windows simply. Supports tkinter, Qt, WxPython, Remi (in browser). Create GUI applications trivially with a full set of widgets. Multi-Window applications are also simple. 3.4 to 3.11 supported. 325+ Demo programs & Cookbook for rapid start. Extensive docs

Transforms the tkinter, Qt, WxPython, and Remi (browser-based) GUI frameworks into a simpler interface. The window definition is simplified by using Python core data types understood by beginners (…

Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)

Hi there! You might find this resource helpful if: Some options you can use from your browser: For other options, see: It won't take long. It's a beautiful introduction ... Try not to drool too much!…

Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)

Turi Create simplifies the development of custom machine learning models.

Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similari…

The Unified Machine Learning Framework

Ivy is an ML framework that currently supports JAX, TensorFlow, PyTorch, and Numpy. We’re very excited for you to try it out! The docs are split into a number of sub-pages explaining different aspect…

Minimal and clean examples of machine learning algorithms implementations

A collection of minimal and clean implementations of machine learning algorithms.

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…

Data-centric declarative deep learning framework

The configuration declares the input and output features, with their respective data types. Users can also specify additional parameters to preprocess, encode, and decode features, load from pre-trai…

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…

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Pattern is a web mining module for Python. It has tools for: It is well documented, thoroughly tested with 350+ unit tests and comes bundled with 50+ examples. The source code is licensed under BSD. …

Open source annotation tool for machine learning practitioners.

doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence to sequence tasks. So, you can create labeled data f…

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…

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with PyTensor

PyMC (formerly PyMC3) is a Python package for Bayesian statistical modeling focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensi…