PCA For Dimension Reduction And Visualization, Temperature-Yield Prediction Via Linear Regression, And Linear Fit Optimization Using Gradient Descent.

This repository consists of Lab Assignments for course Machine Learning.

This repository consists of Lab Assignments for course Machine Learning for Data Mining.

Machine Learning / Gradient Descent

Implementing the gradient descent algorithm from scratch to perform univariate linear regression to analyze the profit made by a bike sharing company.

Solved tasks of "Machine Learning" course, contains implementations of main machine learning algorithms.

Gradient Descent is the process of minimizing a function by following the gradients of the cost function. This involves knowing the form of the cost as well as the derivative so that from a given point you know the gradient and can move in that direction, e.g. downhill towards the minimum value.

Is there a linear connection between immigration and unemployment rate? Let's implement LR and check!

Applying Gradient Descent from scratch and analyzing the effect of changing the number of epochs and learning rate on the mean square error (MSE).

An easy implementation of the GD implementation, comparison using different functions using fixed alpha or the alpha obtained through backtracking algo

Python code for visualizing Gradient Descent optimization paths with animated contours. Demonstrates two strategies: fixed and optimal step sizes. Includes Fibonacci search for step size and data saved with Pickle.

About my Machine Learning Class Assignments.

Created following @StephenGrider Udemy's course