The Best 632 Machine learning Libraries

632 Components & Libraries

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Machine learning Repositories

A handpicked collection of resources for Python developers in data engineering, machine learning, and AI. Inside, you'll discover a neatly arranged selection of frameworks, libraries, and tools crucial for machine learning, ETL, ORM, data/schema validation, database migration, and more, all focused on Python.

Welcome to my repository of Data Engineering with Python resources! Throughout my time as a Data Engineer, I've gathered many bookmarks and resources that have really helped me learn and do my job. I…

Repo where I recreate some popular machine learning models from scratch in Python

This repository is for educational purposes. While the efficiency of the code or completeness is not as good as the one you could find in a library like sklearn, the simplification of the algorithm a…

The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.

The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and ML engineers to red team foundation models and their applica…

Stock-Prediction-Neural-Network-and-Machine-Learning-Examples

Examples of python neural net and ML stock prediction methods with sample stock data.

Simple ML and NN methods for those looking to learn new techniques for stock prediction. These examples are meant to be easy to understand and highlight the essential components of each method. Examp…

AutoML Web App - build Machine Learning pipeline in automatic way with Graphical User Interface (GUI). You can run app locally!

This is a Web Application designed to train Machine Learning pipelines using MLJAR AutoML, specifically tailored for tabular data. All the generated models are compressed into an archive format, allo…

NeuralFoil is an airfoil aerodynamics analysis tool using physics-informed machine learning, in pure Python/NumPy.

NeuralFoil comes with 8 different neural network models, with increasing levels of complexity: This spectrum offers a tradeoff between accuracy and computational cost. Using NeuralFoil is dead-simple…

A delightful collection of free resources and tutorials for Python, data science, and machine learning. Dive into the world of coding, uncover the secrets of data analysis, and unleash the power of machine learning with our beginner-friendly materials. Join our community of learners and let's spoon-feed your curiosity together! 🥄🐍📊🤖

🥄🐍📊🤖 DataMastermind is your go-to repository for learning Python, mastering data science, and exploring the fascinating world of machine learning. Whether you're a beginner or looking to level up you…

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

Time-series machine learning at scale.

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

MindWave is an open-source project designed for beginners to learn about data science, machine learning, deep learning, and reinforcement learning algorithms using Python. The project offers a platform for implementing relevant algorithms, with open-source tools and libraries.

Data Science, Machine Learning, Deep Learning, Reinforcement Learning, and Open Source are all closely related, each building on the foundation of the previous concept. Data Science involves the use …

A performance library for machine learning applications.

You can also install Trident using pip.

A Python toolkit for analyzing machine learning models and datasets.

A Python toolkit for introspection of machine learning models and datasets. To run the notebook examples, try this instead: Start the notebook:

A framework to empower forecasting using Large Language Models (LLMs)

Given the stochastic nature of large language models, individual data points may vary. However, if a sufficient number of agents are employed, the generated models can effectively support comparative…

An ever-evolving introduction to ChatGPT, AI, and machine learning (including prompt examples and Python-built chatbots)

Learn how to use ChatGPT's prompt portal and API, whether you're new to AI or trying to build your first chatbot. The goal of this open-source guide is to establish foundational knowledge of ChatGPT …

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

TPOT stands for Tree-based Pipeline Optimization Tool. TPOT2 is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. Consider TPOT2 your Data …

Powerful machine learning library for Node.js – uses Python's scikit-learn under the hood.

All class names, method names, attribute (accessor) names and types are the same as the official Python version. The main differences are: The Python ML ecosystem is generally a lot more mature than …

PyRCA: A Python Machine Learning Library for Root Cause Analysis

The adoption of microservices architectures is growing at a rapid pace, making multi-service applications the standard paradigm in real-world IT applications. Typically, a multi-service application c…

Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖

Temporian is currently available for Linux and MacOS (ARM and Intel). Windows support is under development. Our goal is to compute the sum of revenue for each store at 11 pm every weekday (excluding …

Algorithmic Trading in Python with Machine Learning

With PyBroker, you'll have all the tools you need to create winning trading strategies backed by data and machine learning. Start using PyBroker today and take your trading to the next level! Or you …

A 50-Day Guide to Becoming a Data Scientist with Python, SQL, and Machine Learning

Welcome to the Data Science course! Over the next 50 days, you will learn a wide range of topics related to Python programming, data science, and machine learning. These topics will be covered in a v…

A lightweight logger for machine learning teams to log images and predictions in production.

The primary goal of this library is to empower machine learning teams to log images and predictions, ensuring their computer vision models are working as intended. Without proper monitoring, small is…

Python-MachineLearning-DeepLearning-Resources

In this repository, you can find links that I find useful in the fields of python, machine learning and deep learning that you can access for free. I will update regularly, feel free to contribute too.

The easier way to do machine learning in Python without coding!

Then in order to have the platform running you need to run one by one all of them, we are working in one unique executable to make your life easy. Let's take a look at our high level architecture

Spatial Representations for Artificial Intelligence - a Python library toolkit for geospatial machine learning focused on creating embeddings for downstream tasks

For future releases, we plan to add more functionalities, such as: The following optional dependencies can be installed to enable additional functionality: Regionalization is a process of dividing a …

stocks-prediction-Machine-learning-RealTime-TensorFlow

Predict operation stocks points (buy-sell) with past technical patterns, and powerful machine-learning libraries such as: Sklearn.RandomForest , Sklearn.GradientBoosting, XGBoost, Google TensorFlow and Google TensorFlow LSTM..Real time Twitter:

Any other kind of contact with us, please go to the ISSUES tab. The stock market is moved by technical indicators, there are several types of volatility, cycle volume, candlesticks, supports, resista…

A geospatial raster processing library for machine learning

When geospatial raster data is concerned in a machine learning pipeline, it is often required to extract meaningful features, such as vegetation indices (e.g., NDVI, EVI, NDRE, etc.) or textures. Thi…

Machine-Learning-Specialization-Coursera

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

This Course is a best place towards becoming a Machine Learning Engineer. Even if you're an expert, many algorithms are covered in depth such as decision trees which may help in further improvement o…

The Python API to run machine learning in your cloud

Here's how you can get started: For example, we can define a pipeline that trains a model on Kubernetes using a GPU and validates that model in AWS Lambda in a few lines of Python: Once you publish t…

A pure-functional implementation of a machine learning transformer model in Python/JAX

Given only a few simple BLAS-like functions: The loss and its gradient needs a few more lines: The random initialization is also short: Add an optimizer, and we are pronto a romblare.