Ml Libraries

308 Components & Libraries

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Ml Libraries

An Open Source Machine Learning Framework for Everyone

TensorFlow was originally developed by researchers and engineers working within the Machine Intelligence team at Google Brain to conduct research in machine learning and neural networks. However, the…

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…

☁️ Build multimodal AI applications with cloud-native stack

Jina provides a smooth Pythonic experience for serving ML models transitioning from local deployment to advanced orchestration frameworks like Docker-Compose, Kubernetes, or Jina AI Cloud. Jina makes…

Kodi is an award-winning free and open source home theater/media center software and entertainment hub for digital media. With its beautiful interface and powerful skinning engine, it's available for Android, BSD, Linux, macOS, iOS, tvOS and Windows.

Created in 2003 by a group of like minded programmers, Kodi is a non-profit project run by the XBMC Foundation and developed by volunteers located around the world. More than 500 software developers …

🏆 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…

PRML algorithms implemented in Python

Python codes implementing algorithms described in Bishop's book "Pattern Recognition and Machine Learning" From the table below, you can open the notebooks for each chapter in each of these environme…

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…

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…

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…

Cool open source projects. Choose your project and get involved in Open Source development now.

If you're interested in Open Source and thinking about joining the community of developers, you might find a suitable project here.

Integrated set of Django applications addressing authentication, registration, account management as well as 3rd party (social) account authentication.

Integrated set of Django applications addressing authentication, registration, account management as well as 3rd party (social) account authentication. Most existing Django apps that address the prob…

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…

🔥 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 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…

CLI tool and python library that converts the output of popular command-line tools, file-types, and common strings to JSON, YAML, or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts.

JSON Convert or using the alternative "magic" syntax: See also: Use Cases: For example, to skip the first and last line of the following text, you could express the slice in a couple ways: Here is a …

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

There are several ways to get in touch with us:

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, w…

The awesome document factory

WeasyPrint is a smart solution helping web developers to create PDF documents. It turns simple HTML pages into gorgeous statistical reports, invoices, tickets… From a technical point of view, WeasyPr…

Performant type-checking for python.

We start by creating an empty project directory and setting up a virtual environment: Next, we teach Pyre about our new project: We are now ready to run Pyre: Pyre is licensed under the MIT license.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

GitHub GitHub issues -- file bug reports / track issues here Stack Overflow -- ask all code/software questions here Cross Validated (Stack Exchange) -- ask algorithm/theory questions here h2ostream G…

Preview GitHub README.md files locally before committing them.

Render local readme files before sending off to GitHub. Sometimes you just want to see the exact readme result before committing and pushing to GitHub. To install grip, simply: On OS X, you can also …

Python code for "Probabilistic Machine learning" book by Kevin Murphy

The notebooks needed to make all the figures are available at the following locations. You can use any of the following options to install the other requirements. Run Then install manually.

A flexible, high-performance serving system for machine learning models

To note a few features: The easiest and most straight-forward way of using TensorFlow Serving is with Docker images. We highly recommend this route unless you have specific needs that are not address…

Feature Store for 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…

Emacs client/library for the Language Server Protocol

Contributions are very much welcome!

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

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…

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