2. Pandas for ML: Reading & Saving Data

Statistics 1- Revision Week 1 - 4

Numpy in 2 minutes: numpy version, path and upgrade

Numpy in 2 minutes: np.random.permutation()

Feature and Label Matrix

6. Scikit-learn for ML: fetch_openml

5. Scikit-learn for ML: fetch dataset

4. Scikit-learn for ML: Data Loading

3. Scikit-learn for ML: make_blobs

2. Scikit-learn for ML: make_classification

1. Scikit-learn for ML: make_regression

0. Scikit-learn for ML: Datasets Overview

0. Pandas for ML: Course Overview

6. Pandas for ML: Boolean Series and Indexing

5. Pandas for ML: Data Selection using loc and iloc

4. Pandas for ML: Three Step Routine

3. Pandas for ML: Dataframe and Series

2. Pandas for ML: Reading & Saving Data

1. Pandas for ML: Introduction to Pandas

0. Course Overview

4. numpy Indexing

6. Summary

5. numpy Selection and Saving

3. Useful numpy methods

2. Nine Ways to Create numpy Array