Mac Libraries

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Mac Libraries

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…

:mag: Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT and alike). Haystack offers production-ready tools to quickly build complex question answering, semantic search, text generation applications, and more.

This command installs everything needed for basic Pipelines that use an in-memory DocumentStore. If you want to install only the dependencies needed for model inference on your local hardware (not re…

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…

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.

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. You can create labeled data for …

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 python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

An open-source python library built to empower developers to build applications and systems with self-contained Deep Learning and Computer Vision capabilities using simple and few lines of code. We t…

A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley II, 2018.

Join our Telegram discussion group to ask any questions you have about Video2X, chat directly with the developers, or discuss about upscaling technologies and the future of Video2X in general. The fo…

🔥 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…

A supercharged Git/GitHub command line interface (CLI). An official integration for GitHub and GitHub Enterprise: https://github.com/works-with/category/desktop-tools

Run Python commands alongside shell commands: Color options include: Usage: View all pull requests for your repos: View all open issues where you have been mentioned: View all issues, filtering for o…

: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…

:speech_balloon: Machine Learning Course with Python:

The purpose of this project is to provide a comprehensive and yet simple course in Machine Learning using Python. Please consider the following criterions in order to help us in a better way: We are …

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

pix2tex: Using a ViT to convert images of equations into LaTeX code.

The goal of this project is to create a learning based system that takes an image of a math formula and returns corresponding LaTeX code. To run the model you need Python 3.7+ Model checkpoints will …

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…

Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!

Development work has resumed on the framework with the aim of bringing it into 2020: Python 3.8+, Less Dependencies, Ease of Use (Installer, GUI) and much more! Still open-source with a permissive li…

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…

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.

macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.

Run all: To update later on, just run that command again. Alternatively, to update while avoiding the confirmation prompt: To sync dev-setup to your local home directory without Git, run the followin…

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

A Mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning. Machine Learning is a subfield of computer science that gives computers the ability to learn without being explic…

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…

A log of things I'm learning

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