machine-learning
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Repositories (1435)
captcha break based on opencv2, tesseract-ocr and some machine learning algorithm.
Stanford Code From Cars That Entered DARPA Grand Challenges
An ongoing list of pandas quirks
Java Statistical Analysis Tool, a Java library for Machine Learning
Machine Learning Problem Bible | Problem Set Here >>
An evolving guide to learning Deep Learning effectively.
Food Classification with Deep Learning in Keras / Tensorflow
OpenCV projects: Face Recognition, Machine Learning, Colormaps, Local Binary Patterns, Examples...
TonY is a framework to natively run deep learning frameworks on Apache Hadoop.
Framework and Library for Distributed Online Machine Learning
ML-Ensemble – high performance ensemble learning
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
The MobileNet neural network using Apple's new CoreML framework
A scikit-learn based module for multi-label et. al. classification
Bayesian Text classification service based on Redis and Python/Tornado
Pool-based active learning in Python
Optical Character Recognition in Swift for iOS&macOS. 银行卡、身份证、门牌号光学识别
Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
Deep neural network framework for multi-label text classification
Survival analysis built on top of scikit-learn
A Real-time Mario Kart 64 AI using ConvNets.
Code for Kaggle Data Science Competitions
This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way
Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Paramet...
《机器学习宝典》包含：谷歌机器学习速成课程（招式）+机器学习术语表（口诀）+机器学习规则（心得）+机器学习中的常识性问题 （内功）。该资源适用于机器学习、...
Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA
State of AI
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
Python implementation of KNN and DTW classification algorithm
Temporary home for fastai v2 while it's being developed
Preparing for machine learning interviews
Lazydata: Scalable data dependencies for Python projects
Resources, datasets, papers on Question Answering
Python package for stacking (machine learning technique)