Machine-learning-Equations for Andrew Ng Coursera course in Python

1. Univariate Linear Regression::- Univariate Linear regression.ipynb

-- It covers basic numpy required for writing machine learning equations for Univariate linear regression. It also include Hypothesis, Cost function and Gradient descent equations of Univariate linear regression. YouTube link for Univariate linear regression

2. Multivariate Linear Regression::-Multivariate linear Regression.ipynb

• It includes Hypothesis, Cost function, Gradient descent equations, feature normalization and R2 score of Multivariate linear regression.It also covers mathematical derivation and writing machine learning equations for Multivariate linear regression.YouTube link for Multivariate linear regression

3. Normal equation derivation for linear regression.Normal Equation for Linear regression.ipynb -- It covers derivation and writing Normal equations for closed formed linear regression.YouTube Link for Normal Equation

4. Logistic regression from scratch.LogisticRegression.ipynb -- It contain sigmoid function, cost function, and gredient descent visualization. It also includes intuition, mathametical derivation and writing machine learning equations for logistic regression.YouTube Link for Logistic Regression

5. Logistic regression with regularization from scratch.Logistic Regression with Regularization.ipynb -- It covers writing machine learning equations for Regularization in logistic #regression. It covers intuition, and how regularization aids to avoid Overfitting in the data. It also includes visualization of Lambda showing Overfitting and Underfitting cases using Andrew Ng Coursera dataset in python.YouTube link for Logistic Regression with Regularization

6. MultiClass Classification in logistic Regression & OneHotEncoding from Scratch:-MultiClass Classification using logistic regression.ipynb -- It covers major concept of Multiclass classification model and OneHotEncoding intuition.YouTube Link MultiClass Classification using logistic regression

7. Neural Network from Scratch (Feedforward and Backward Propagation:-Feedforward Implementation ( Neural Network).ipynb -- It covers both theory and implementation of Feedforward Propagation Neural Network from Scratch.YouTube Link Feedforward Propagation

BackPropagation (Neural Network).ipynb -- It covers both theory and implementation of BackPropagation Neural Network from Scratch.YouTube Link BackPropagation