AI Theory and CodingRegression and Gradient Descent

Dig deep into regression and learn about the gradient descent algorithm. This course does not rely on high-level libraries like scikit-learn, but focuses on building these algorithms from scratch for a thorough understanding. Master the implementation of simple linear regression, multiple linear regression, and logistic regression powered by gradient descent.

Unveiling the Magic of Sales Prediction

Predicting Sales Using Simple Linear Regression Constants

Calculating the Coefficients of Linear Regression

Mysterious Prediction Model Failure

Determining House Prices with Multiple Features

Rectifying House Price Predictions in Space Real Estate Market

Predicting Housing Prices with Multiple Linear Regression

Calculating Coefficients in Multiple Linear Regression

Adjust the Learning Rate

Applying Gradient Descent in Real Estate Pricing

Implementing Gradient Descent in Real Estate Analysis

Trying New Approach

Sigmoid Function: From Input to Probability

Implementing the Sigmoid Function

Evaluating Spam Filter Accuracy with Logistic Regression

Adding the Gradient to Logistic Regression

Implementing the Sigmoid Function in Logistic Regression