advancepython

Advanced python exercises.

angular

arithmetic_expre

awesome-nlp

bookshelf

bootstrap4

c-exercise

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

chess

cnn

cookiecutter-pypackage

Cookiecutter template for a Python package.

cracking-the-coding-interview-6th-edition

decisiontree

deployment

dongxiaohuang

dongxiaohuang.github.io

enigma

gaussianprocesses

iota

iotachart

leetcode_solutions

linear-models

ICDSS Machine Learning Workshop Series: Linear Models

linkcharity_production

linkingcharities

m0jax999429

Config files for my GitHub profile.

mcmc

mocha-learning

mocha is a javascript unit test tool

naive-bayesian-networks

The coursework for the Intelligent Data Analysis and Probabilistic Inference Course has two objectives. Firstly it is intended to help you fully understand some of the algorithms covered in the course by doing some practical data analysis work, and secondly it serves as an introduction to Python which is an excellent environment for doing numerical analysis. Python has a powerful syntax that allows you to write code that looks very much like the equations found in the notes. It provides an interface to a highly robust and fast numerical programming library. The syntax has some similarities to Matlab but Python is available for free. There are many good online tutorials which you may want to work through if you find the coursework notes too terse.

neural_network

nodejs

Server-side Development with NodeJS, Express and MongoDB