aufawibowo's Stars
jwasham/coding-interview-university
A complete computer science study plan to become a software engineer.
donnemartin/system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
getify/You-Dont-Know-JS
A book series on JavaScript. @YDKJS on twitter.
veggiemonk/awesome-docker
:whale: A curated list of Docker resources and projects
adam-golab/react-developer-roadmap
Roadmap to becoming a React developer
andkret/Cookbook
The Data Engineering Cookbook
kmario23/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
cncf/landscape
🌄 The Cloud Native Interactive Landscape filters and sorts hundreds of projects and products, and shows details including GitHub stars, funding, first and last commits, contributor counts and headquarters location.
symfony/http-foundation
Defines an object-oriented layer for the HTTP specification
symfony/finder
Finds files and directories via an intuitive fluent interface
symfony/http-kernel
Provides a structured process for converting a Request into a Response
webmozarts/assert
Assertions to validate method input/output with nice error messages.
github/personal-website
Code that'll help you kickstart a personal website that showcases your work as a software developer.
symfony/debug
Provides tools to ease debugging PHP code
microsoft/tensorwatch
Debugging, monitoring and visualization for Python Machine Learning and Data Science
symfony/event-dispatcher-contracts
A set of event dispatcher abstractions extracted out of the Symfony components
Pungyeon/clean-go-article
A reference for the Go community that covers the fundamentals of writing clean code and discusses concrete refactoring examples specific to Go.
Cartucho/mAP
mean Average Precision - This code evaluates the performance of your neural net for object recognition.
vineetjohn/daily-coding-problem
Solutions to problems sent by dailycodingproblem.com
javascript-tutorial/id.javascript.info
Tutorial JavaScript Modern dalam Bahasa Indonesia
lephleg/laravel-lumen-docker
Laravel/Lumen Docker Scaffold
rasbt/uw-madison-datacience-club-talk-oct2019
Slides and code for the talk at UW-Madison's Data Science Club, 10 Oct 2019
xingxingso/Laravel-5.7-From-Scratch
Laravel 5.7 From Scratch
benkoo/TensorCloud
A set of open-sourced computational services orchestrated by a tensor-based metalanguage.
innossh/docker-compose-example
mocatfrio/distributed-database
Distributed Database Course 2018
aufawibowo/deepstock
Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:
aufawibowo/Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
aufawibowo/StockMarketGAN
Stock Market Prediction Using Unsupervised Features
aufawibowo/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.