A collection of infrastructure and tools for research in neural network interpretability.

Hyperparameter Optimization for Keras Models

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

Open Source Fast Scalable Machine Learning Platform For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Mean…

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Official Kaggle API

Deep Learning Book Chinese Translation

Set up commonly used 📦 components

Deep Learning Specialization by Andrew Ng on Coursera.

Public repo containing code to train, visualize, and evaluate semi-supervised topic models and baselines for regression/classification on labeled bag-of-words dataset, as described in Hughes et al.…

These are my personal notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The …

Keras package for deep residual networks

Automatically exported from code.google.com/p/word2vec

Application CI/CD on OpenShift with Jenkins

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

Essential Cheat Sheets for deep learning and machine learning researchers

Stanford CS224n: Natural Language Processing with Deep Learning

MACS -- Model-based Analysis of ChIP-Seq

Peer Assessment 1 for Reproducible Research

Plotting Assignment 1 for Exploratory Data Analysis