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2015

Public material for CS109

2018-cs109a

Repository for CS109A Fall 2018

2019-cs109a

https://harvard-iacs.github.io/2019-CS109A/

2019-cs109b

2020-cs109a

2021-cs109a

2021-cs109b

algorithms---coursera

Python implementations of Coursera Algorithms Specialization by Stanford University

analytics-edge

coursera---deep-learning-specialization

Modeling Neural Networks from first principles

coursera-applied-data-science-with-python

Repository for coursera specialization Applied Data Science with Python by University of Michigan

coursera-stanford-ml-python

Coursera/Stanford Machine Learning course assignments in python

cs209-data-science

This repo contains a series of data science courses from Harvard. What's special about these three courses is that the course content is the most complete one I've ever seen.

dat8

General Assembly's Data Science course in Washington, DC

data-science-from-scratch

code for Data Science From Scratch book

data-science-in-tidyverse

Materials for Data Science in the Tidyverse, a two-day workshop @ rstudio:conf(2019)

data-structure-and-algorithms-in-python

Data Structure and Algorithms for interview preparation.

data-structures-and-algorithms

Overview of data structures and algorithms

deep-learning-coursera

Deep Learning Specialization by Andrew Ng, deeplearning.ai.

econometrics-with-python

Tutorials of econometrics featuring Python programming. This is a crash course for reviewing the most important concepts and techniques of basic econometrics, the theories are presented lightly without hustles of derivation and Python codes are straightforward.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

ipython-notebooks

A collection of IPython notebooks covering various topics.

machine-learning-models

knn, Regression (LASSO, Ridge), Logistic, Principal component Analysis (PCA), Discriminant Analysis (LDA, QDA), Trees, Random Forest, Boosting

machine_learning_complete

A comprehensive repository containing 30+ notebooks on learning machine learning!

markdown-here

Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.

mba

mbacourse

Material from the Big Data course at Chicago Booth

ml-coursera-python-assignments

Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.

mlcourse.ai

Open Machine Learning Course

neural-networks-intro

Simple first principles models on neural network concepts. Models include perceptron, gradient descent, back propagation, and applying keras and Tensors on datasets.