12.27 Confidence interval using bootstrapping

12.28_Hypothesis testing methodology, Null-hypothesis, p-value

12.29 Hypothesis Testing Intution with coin toss example

12.30 Resampling and permutation test

12.31 K-S Test for similarity of two distributions

12.32 Code Snippet K-S Test

12.33 Hypothesis testing: another example

12.34 Resampling and Permutation test: another example

12.35 How to use hypothesis testing?

12.36 Proportional Sampling

12.37 Revision Questions

– Telegraph
https://telegra.ph/Revision-Questions-02-11

#Module 13 : Interview Questions on Probability and statistics

👉 13.1 Questions

13.1 Questions

Telegraph
https://telegra.ph/Questions-02-11-2

#Module 14 : Dimensionality reduction and Visualization
Section 14 is divided into sub sections

👉 14.1 What is Dimensionality reduction?

👉 14.2 Row Vector and Column Vector

👉 14.3 How to represent a data set?

👉 14.4 How to represent a dataset as a Matrix.

👉 14.5 Data Preprocessing: Feature Normalisation

👉 14.6 Mean of a data matrix

👉 14.7 Data Preprocessing: Column Standardization

👉 14.8 Co-variance of a Data Matrix

👉 14.9 MNIST dataset (784 dimensional)

👉 14.10 Code to Load MNIST Data Set

14.1 What is dimensionality reduction?

14.2 Row vector and Column Vector

14.3 How to represent a data set?

14.5 - Data Preprocessing Feature Normalisation