ML-learning-path

Self learning guide for machine learning

View the Project on GitHub elephantscale/ML-learning-path

Index/ Python Data Analysis

STATS-1: Basic Statistics

Generic

Population vs. Sample

Variable Types

Numerical Data Analysis

Summarizing/Describing Data

Covariance / Correlation

Exploratory Data Analytics

Check List

You should be familiar with the following

Exercises

These are simple exercises designed to reinforce your learning so far.

Difficulty Level

★☆☆ - Easy
★★☆ - Medium
★★★ - Challenging
★★★★ - Bonus

EX-1 - Mean / Median / STD (★☆☆)

We have some sample salary data (in thousands) from two cities.

city1 = [15,12, 20, 25, 50, 35, 75, 80, 60, 45, 36]
city2 = [40,42, 45, 60, 55, 52, 56, 52, 62, 57, 48]

Calculate mean, median, variation, standard deviation for both city data.

EX-2 - NBA Player Stats (★★☆)

EX-3 - Correlation of NBA Player Stats (★★☆)

EX-4 - Correlation Matrix for House Sales Data (★★☆)

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