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awesome-deep-learning-resources

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier

book-cryptocurrency

capstonecoursera

Data Science Specialization Coursera - Capstone Project - mhnierhoff

ccxt

A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges

courserajhudatasciencecapstone

Capstone Project for the Coursera JHU Data Science Specialization

cryptocurrency-trading-bot

bot for cryptocurrency trading

cv_examples

cv_web

computer vision web application

cvlecture_opencv_webapp

data-science-capstone

The Swiftkey Capstone project for the Coursera Data Science Specialization

dscapstone

coursera data science capstone - swiftkey

dscapstone-1

Coursera/Johns Hopkins Data Science Cert Capstone

dsci-benchmark

R scripts for benchmarking next word prediction algorithms developed for the Coursera Data Science Capstone Project.

eosio-web-ide

eosio-web-ide

har-stacked-residual-bidir-lstms

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

how-to-grow-neat-software-architecture-out-of-jupyter-notebooks

Growing the code out of your notebooks - the right way.

human-activity-recognition

Recognizing human activities using Deep Learning

iot-db410c-course-4

In this repository, you will find the code for Internet of Things Course 4: VoIP on coursera.org

lstm-human-activity-recognition

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

ml-blocks

Machine Learning Blocks game

multi-temporal-scale

learning multi-temporal-scale deep information for action recognition

neuraxle

A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.

pykrx

KRX 주식 정보 스크래핑

r-marketing-analysis-packages

A list of R Packages for marketing tools & analysis

r2c

Recognition to Cognition Networks (code for the model in "From Recognition to Cognition: Visual Commonsense Reasoning", CVPR 2019)

seq2seq-signal-prediction

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

try-django

[Newest Version] - Learn Django bit by bit in this series

typeahead.js-for-shiny

This project aimed to provide an intuitive, familiar, and easy-to-use Google-like "suggestion" box predicting the next word a user would type for Johns Hopkins University Data Science Specialization's capstone project. The code was split to give here a minimal but functional demo showcasing the typeahead.js and Shiny integration.