Repository Index

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

• ml
• data-science
• machine-learning
• machine-learning-algorithms

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

• machine-learning
• deep-learning
• deep-reinforcement-learning
• machine-learning-from-scratch

Best Practices on Recommendation Systems

• machine-learning
• recommender
• ranking
• deep-learning

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

• machine-learning
• trading
• investment
• finance

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

• machine-learning
• deep-learning
• data-analysis
• data-mining

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

• machine-learning
• machine-learning-algorithms
• logistic-regression
• data-science

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

• numpy
• python
• linear-algebra
• data-science

Open Machine Learning Course

• machine-learning
• data-analysis
• data-science
• pandas

Statistical Machine Intelligence & Learning Engine

• machine-learning
• regression
• clustering
• manifold-learning

Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark

• spark
• pyspark
• azure
• scala

StellarGraph - Machine Learning on Graphs

• graphs
• machine-learning
• machine-learning-algorithms
• graph-convolutional-networks

Quantitative analysis, strategies and backtests

• quantitative-finance
• quantitative-trading
• portfolio-management
• risk-management

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

• machine-learning
• data-science
• r
• python

oneAPI Data Analytics Library (oneDAL)

• onedal
• data-analysis
• oneapi
• machine-learning

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

• data-analytics
• data-cleaning
• data-cleansing
• data-engineering

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

• feature-selection
• data-science
• python

Python-based implementations of algorithms for learning on imbalanced data.

• data-science
• machine-learning
• imbalanced-data
• notre-dame

A fast xgboost feature selection algorithm

• machine-learning
• machine-learning-algorithms
• feature-selection
• xgboost-algorithm

AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.

• ai
• algorithmic-trading
• crypto
• machine-learning

Python implementation of the goldeneye algorithm to investigate how classifiers utilise the structure of a dataset.

• data-science
• model-explanation

Implementation of Partitioning Around Medoids (PAM) in H2O-3

• clustering
• machine-learning
• h2o-3
• java