hbcbh1999 Goto Github PK

craigslist-clone

railslist is a craigslist clone

crazeeriderbbc

Crazee Rider - BBC Micro

create-react-app

Create React apps with no build configuration.

cri-containerd

Containerd-based implementation of Kubernetes Container Runtime Interface

crouton

Chromium OS Universal Chroot Environment

crypto-algorithms

Basic implementations of standard cryptography algorithms, like AES and SHA-1.

crypto-bar

📈 A menu bar app that updates cryptocurrencies prices in real-time

crypto-for-kids

A cryptography book for kids

crypto-rnn

Learning the Enigma with Recurrent Neural Networks

cryptocompare

Haskell wrapper for the CryptoCompare API, a source of crypto-currency information and price data

cryptoplace

crystal

The Crystal Programming Language

cs-video-courses

List of Computer Science courses with video lectures.

cs109-groupproj-college

Harvard CS109 Group Project Fall 2015 -- Barred Gates: Predicting College Admissions

cs181-s16

Machine Learning at Harvard

cs20si

My solutions to Stanford's CS20si: Tensorflow for Deep Learning Research.

cs20si-examples

Example of stanford cs20si for learning purpose

cs221-car

This assignment is a modified version of the Driverless Car assignment written by Chris Piech. A study by the World Health Organisation found that road accidents kill a shocking 1.24 million people a year worldwide. In response, there has been great interest in developing autonomous driving technology that can can drive with calculated precision and reduce this death toll. Building an autonomous driving system is an incredibly complex endeavor. In this assignment, you will focus on the sensing system, which allows us to track other cars based on noisy sensor readings. Getting started. Let's start by trying to drive manually: python drive.py -l lombard -i none You can steer by either using the arrow keys or 'w', 'a', and 'd'. The up key and 'w' accelerates your car forward, the left key and 'a' turns the steering wheel to the left, and the right key and 'd' turns the steering wheel to the right. Note that you cannot reverse the car or turn in place. Quit by pressing 'q'. Your goal is to drive from the start to finish (the green box) without getting in an accident. How well can you do on crooked Lombard street without knowing the location of other cars? Don't worry if you aren't very good; the staff was only able to get to the finish line 4/10 times. This 60% accident rate is pretty abysmal, which is why we're going to build an AI to do this.

cs221-logic

In this assignment, you will get some hands-on experience with logic. You'll see how logic can be used to represent the meaning of natural language sentences, and how it can be used to solve puzzles and prove theorems. Most of this assignment will be translating English into logical formulas, but in Problem 4, we will delve into the mechanics of logical inference.

cs221_notes

All of the lecture notes from CS221: Artificial Intelligence

cs224n-gpu-that-talks

Repository for CS224n project - Attention, I'm Trying to Speak : Speech Synthesis

cs224n-winter-2017

All lecture notes, slides and assignments from CS224n: Natural Language Processing with Deep Learning class by Stanford

cs224n_project

Neural Image Captioning in TensorFlow.

cs229

Stanford CS229 (Autumn 2017)

cs229-machine-learning-stanford-fall-2016

CS229 Machine Learning Class.

cs229-ps

Stanford Machine Learning course CS229(2017) Problem set answers

cs229-python-kit

A kit of starter code for CS229 Machine Learning course problem sets

cs229_ml

🍟 Stanford CS229: Machine Learning

cs229_notes

All of the lecture notes from CS229: Machine Learning

cs230-code-examples

Code examples in pyTorch and Tensorflow for CS230