sylvaticus/MITx_18.6501x_fundamental_of_statistics

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sylvaticus/MITx_18.6501x_fundamental_of_statistics

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Students notes on the MITx course 18.6501x "Fundamental of Statistics"

MITx_6.86x

Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning

BetaML.jl

Beta Machine Learning Toolkit

juliatutorial

A tutorial for the Julia language inspired by the Python tutorial

Jupyter Notebook

SPMLJ

Introduction to Scientific Programming and Machine Learning with Julia

StrategicGames.jl

A set of functions in pure Julia for Game Theory

OdsIO.jl

ODS (LibreOffice, OpenOffice and many more..) I/O for Julia using the python ezodf module

LAJuliaUtils.jl

Utility functions for Julia, mainly dataframes operations

MyAwesomePackage.jl

A dummy package for the Julia Concise Tutorial

MITx-MicroMaster-Statistics-and-Data-Science

Cheatsheets for the subjects in the MITx MicroMaster in Statistics and Data Science

JuliaMLCourse

Introduction to Scientific Programming and Machine Learning with Julia

commonDistributionsInJuliaPythonR

Common probability distributions in Julia, Python and R

MITx_-_6.041x_Introduction_to_Probability

Cheatsheets for the MITx course 6.041x "Introduction to Probability"

IntroductionToProbability

Clone of the (now open-sourced) Grinstead and Snell 1998 "Introduction to probability" book and related algorithms

GameTheoryNotes

Student's note on Game Theory, mainly from the Coursera "Game Theory" (Jackson, Leyton-Brown & Shoham) MOOC

14_310x_ClassNotes

Class notes for 14_310x