Training Very Deep Neural Networks Without Skip-Connections

Preparing for machine learning interviews

Korean BERT pre-trained cased (KoBERT)

Simple but useful Python web scraping tutorial code.

this repository accompanies the book "Grokking Deep Learning"

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Bayesian Deep Learning Benchmarks

提供对YOLOv3及Tiny的多种剪枝版本，以适应不同的需求。

A pedagogical implementation of Autograd

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Data Analysis Baseline Library

Recipes for using Python's pandas library

The codes I made while I practiced various TensorFlow examples

Proposes neural networks that can generate animation of virtual characters for different actions.

Python Deep Dive Course - Accompanying Materials

coursera吴恩达机器学习课程作业自写Python版本+Matlab原版

A TensorFlow implementation of DeepMind's Differential Neural Computers (DNC)

Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library

Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"