Introduction
- Introduction
- Why Statistics?
- Types of variables
- Variable Types Quiz
Introduction to Linear Regression
- Linear Regression Introduction
- R-Squared
- SSE_SST_SSE
- Cost-Function and Optimization
- Cost-Function in 3-d
- Gradient Descent Maths
- Gradient Descent Example
coding a linear regression model from scratch
- coding a linear regression model from scratch
- house price prediction with linear regression
- Effect of learning rate in gradient descent
- adaptive learning rates
- multivariate linear regression
- coding multivariate linear regression from scratch
Basic Statistics
- Linear Regression prerequisites: statistics
- What is hypothesis
- Unbiased sample estimator
- Histogram and Distributions
- P-Value and Testing hypothesis
- Normal Distribution Yet another example
Statistical Tests
- Types of Test for hypothesis
- Problem Statement
- T-Statistics
- T-test in python
- Z- Test
- Chi-Square Test
Assumptions of linear regression
- Introduction to Assumptions of Linear regression
- correlation and covariance
- Assumptions of linear regression
- VIF and multicollinearity
- upcoming-lectures
Logistic Regression
- Logistic regression binary classification
- Logistic regression multiclass classification
Bonus Lectures
- Eigenvalues and Eigenvectors
- make moving charts with python
- Time Series forecasting
- PCA for data science and Machine learning
- Solve a neural network on paper
- Training Neural network with your own images
- Transfer learning
- Entropy a Mathematical view
- Eyes and Face detection with python
- Data Science Interview Questions
