cyli2019,Chengyin Li,github

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

chemgan-challenge

Code for the paper: Benhenda, M. 2017. ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.

chemopt

Optimizing Chemical Reactions with Deep Reinforcement Learning

chestx-ray-14

Segmentation Guided Thoracic Classification

chexnet-1

Implementation and fullstack pipeline for CheXNet classifier

chexnet-with-localization

Weakly Supervised Learning for Findings Detection in Medical Images

cmu-thesis

Code for Yun Wang's PhD Thesis: Polyphonic Sound Event Detection with Weak Labeling

cnn-for-tumour-classification

Algorithm based on Convolutional Neural Network (CNN) to classify Computed Tomography scans (CT scans) as containing either malignant or benign tumours

cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

code-of-learn-deep-learning-with-pytorch

This is code of book "Learn Deep Learning with PyTorch"

computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

coulomb_matrix

A Python based code to construct a Sorted Coulomb matrix from Smile strings (CSV input) of molecules . An optional scikit-learn is invoked at the end of the script to classify molecules using SVM.

coursera-applied-data-science-with-python

Repository for coursera specialization Applied Data Science with Python by University of Michigan

cs188

UC Berkeley 2018 Fall CS188 : Introduction to Artificial Intelligence

csc

Lesson materials for "Introduction to Python GIS" -course held at CSC Finland.

cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

cyli2019.github.io

A beautiful, simple, clean, and responsive Jekyll theme for academics

d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.