Mastering Python for Data Science

Table of Contents

1. Getting started with Data
2. Getting the larger picture from inferential statistics
3. Finding the Needle in the Haystack with Data Mining
4. Making sense of data through Advanced Visualization
5. Uncovering Machine Learning
6. Performing predictions with Linear Regression
7. Estimating Likelihood with Logistic Regression
8. Generating recommendations with Collaborative Filtering
9. Pushing the boundaries with Ensemble Models
10. Applying Segmentation with K-means clustering
11. Analyzing Unstructured Data with Text Mining
12. Leveraging Python in the World of Big Data