bbyun28 Goto Github PK

cs231n.github.io

Public facing notes page

cs273b

CS273B Deep Learning for Genomics Course Materials

cspade

cutadapt

Cutadapt removes adapter sequences from sequencing reads

cvae

github for "Molecular generative model based on conditional variational autoencoder for de novo molecular design"

cwltool

Common Workflow Language reference implementation

d2

Speed virtual screening by 50X

d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.

data-analysis-and-machine-learning-projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

data-science-from-scratch

code for Data Science From Scratch book

data_curation_workflow

datamol

Molecular Manipulation Made Easy.

dataviz

A book covering the fundamentals of data visualization

dcell

DCell browser and gene deletion simulator

dcnet

Computer vision for differential cell counts in cytopathology images

de-novo-drug-design

Optimizing blood-brain barrier permeation through Deep Reinforcement Learning for de novo drug design

deapp

DEAPP shiny App

debrowser

Differential Count Data Analysis Toolbox

decimer-image_transformer

DECIMER 1.0: Deep Learning for Chemical Image Recognition using Transformers

deelig

Binding Affinity Prediction using Deep learning models

deep-drug-coder

Deep Drug Coder: A TensorFlow2.0 heteroencoder for molecular encoding and de novo generation

deep-drug-response

deep-learning

Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on artificial neural networks. Learning can be supervised, semi-supervised or unsupervised. Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases superior to human experts.

deep-learning-enables-rapid-identificantion-of-potent-ddr1-kinase-inhibitors

try

deep-learning-from-scratch

『밑바닥부터 시작하는 딥러닝』(한빛미디어, 2017)

deep-learning-from-scratch-2

『밑바닥부터 시작하는 딥러닝 ❷』(한빛미디어, 2019)

deep-learning-gene-expression

Implementation of deep learning and machine learning models to translate drug induced changes in gene expression across domains.

deep-learning-keras-tensorflow

Introduction to Deep Neural Networks with Keras and Tensorflow

deep-learning-with-python-notebooks

<케라스 창시자에게 배우는 딥러닝> 도서의 주피터 노트북

deep-molecular-optimization

Molecular optimization by capturing chemist’s intuition using the Seq2Seq with attention and the Transformer