An educational resource to help anyone learn deep reinforcement learning.
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Algorithm and data structure articles for https://cp-algorithms.com (based on http://e-maxx.ru)
- algorithms
- translation
- algorithm-competitions
- algorithms-and-data-structures
FFmpeg libav tutorial - learn how media works from basic to transmuxing, transcoding and more. Translations: 🇺🇸 🇨🇳 🇰🇷 🇪🇸 🇻🇳 🇧🇷 🇷🇺
Good ideas for iOS development, by Futurice developers.
- best-practices
- swift
- objective-c
- ios
This guide details creating a secure Linux production system. OpenSCAP (C2S/CIS, STIG).
TranslatedA programmer who loves cooking and is determined to use animations to explain algorithms in plain, easy-to-understand terms. My interview website: www.chengxuchu.com
- leetcode
- offer
- algorithms
- base
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
- deep-learning
- mit
- self-driving-cars
- deep-reinforcement-learning
:snowflake: a short introduction to node.js
This repository has examples of broken patterns in ASP.NET Core applications
Kubernetes application example tutorials
Go DDD example application. Complete project to show how to apply DDD, Clean Architecture, and CQRS by practical refactoring.
- go
- golang
- ddd
- clean-architecture
From the basics to slightly more interesting applications of Tensorflow
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.
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
Claude Code Guide - Setup, Commands, workflows, agents, skills & tips-n-tricks from beginner to power user!
how to build modular applications with browserify
:earth_americas: Simple and ready-to-use tutorials for TensorFlow
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
- machine-learning
- deep-learning
- lstm
- human-activity-recognition
Quantitative analysis, strategies and backtests
- quantitative-finance
- quantitative-trading
- portfolio-management
- risk-management
TensorFlow Tutorials
- tensorflow-tutorials
- convolutional-neural-networks
- recurrent-neural-networks
A collection of succinct guides - Public Domain
Ruby Tricks, Idiomatic Ruby, Refactoring and Best Practices
Handout for the tutorial "Creating publication-quality figures with matplotlib"
The OWASP NodeGoat project provides an environment to learn how OWASP Top 10 security risks apply to web applications developed using Node.js and how to effectively address them.