Artificial Intelligence Deep Learning Machine Learning Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
Toxic Comment Classification Challenge
Code for 3rd place solution in Kaggle Human Protein Atlas Image Classification Challenge.
Code for Kaggle and Offline Competitions
Girls In Ai
免费学代码系列：小白python入门、数据分析data analyst、机器学习machine learning、深度学习deep learning、kaggle实战
top 1% solution to toxic comment classification challenge on Kaggle.
A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Machine Learning Workflow With Python
This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation
Pin, Discover and Share Resources
1st Place Solution for CrowdFlower Product Search Results Relevance Competition on Kaggle.
Code for 3rd place solution in Kaggle Humpback Whale Identification Challenge.
Code for Kaggle Competitions
Ml Dl Scripts
The repository provides usefull python scripts for ML and data analysis
Ml Fraud Detection
Credit card fraud detection through logistic regression, k-means, and deep learning.
Kaggle Kernel for House Prices competition https://www.kaggle.com/massquantity/all-you-need-is-pca-lb-0-11421-top-4
Cryptocurrency Historical Market Data R Package
Dog Breeds Classification
Set of scripts and data for reproducing dog breed classification model training, analysis, and inference.
Tensorflow implementation : U-net and FCN with global convolution
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
A collection of useful modules and utilities (especially helpful for kaggling) not available in Pytorch
Facial Expression Recognition
Classify each facial image into one of the seven facial emotion categories considered using CNN based on https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge
MLBox is a powerful Automated Machine Learning python library.
Home Credit Default Risk
Default risk prediction for Home Credit competition - Fast, scalable and maintainable SQL-based feature engineering pipeline
Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook
Data Science Bowl 2018
End-to-end one-class instance segmentation based on U-Net architecture for Data Science Bowl 2018 in Kaggle