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Intro

Prerequisites

Python
Math
Software & DevOps
Docker

Topic 1

Topic 1 Intro
Exploratory data analysis with Pandas
Videolecture 1
Demo Assignment 1 Task
Demo Assignment 1 Solution
Bonus Assignment 1

Topic 2

Topic 2 Intro
Visual Data Analysis
Seaborn, Matplotlib, Plotly
Videolecture 2
Demo Assignment 2 Task
Demo Assignment 2 Solution
Bonus Assignment 2

Topic 3

Topic 3 Intro
Classification, Decision Trees & k Nearest Neighbors
Videolecture 3
Demo Assignment 3 Task
Demo Assignment 3 Solution
Bonus Assignment 3

Topic 4

Topic 4 Intro
Ordinary Least Squares
Linear classification
An illustrative example of logistic regression regularization
When logistic regression is good and when it is not
Validation and learning curves
Videolecture 4
Demo Assignment 4 Task
Demo Assignment 4 Solution
Bonus Assignment 4

Topic 5

Topic 5 Intro
Bagging
Random Forest
Feature importance
Videolecture 5
Demo Assignment 5
Demo Assignment 5 Solution
Bonus Assignment 5

Topic 6

Topic 6 Intro
Feature engineering & feature selection
Demo Assignment 6 Task
Bonus Assignment 6

Topic 7

Topic 7 Intro
Unsupervised learning
Videolecture 7
Demo Assignment 7
Demo Assignment 7 Solution
Bonus Assignment 7

Topic 8

Topic 8 Intro
Vowpal Wabbit: Learning with Gigabytes of Data
Videolecture 8
Demo Assignment 8
Demo Assignment 8 Solution
Bonus Assignment 8

Topic 9

Topic 9 Intro
Topic 9. Part 1. Time series analysis in Python
Predicting the future with Facebook Prophet
Videolecture 9
Demo Assignment 9
Demo Assignment 9 Solution
Bonus Assignment 9

Topic 10

Topic 10 Intro
Gradient boosting
Videolecture 10
Demo Assignment 10
Bonus Assignment 10

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By Yury Kashnitsky (yorko)

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