Deep learning Projects

Get Started with Deep Learning

Notebooks explaining various Machine Learning concepts.

Training Repository for my ML and DL notebooks

Construction of a simple feed forward neural network in a Jupyter Notebook

A repository of Jupyter notebooks showcasing a range of PyTorch applications, from foundational concepts and linear regression to neural network models for image classification tasks.

Notebook of experiments and comparison of two different approaches to Coordinate Descent

A hub that contains notebooks that implement Regression models, illustrates LR via Gradient Descent, compares K-means vs Spectral vs Hierarchical, compares PCA vs t-SNE

linear regression implementation with gradient decent

This repository contains a Jupyter notebook that implements Linear Regression using Gradient Descent from scratch. The notebook also includes a comparison of the results with the scikit-learn implementations of Linear, Lasso, and Ridge Regression by plotting graphs.

A notebook with core concepts of gradient descent algorithm to predict the prices for houses in Boston

Jupyter notebooks, scripts, and results associated with the paper Visualization of Optimization Algorithms by Marco Morais (Morais, 2020).

In this notebook, we want to create a machine learning model from scratch to predict car prices using independent variables.

Implementation of classic machine learning concepts and algorithms from scratch and math behind their implementation.Written in Jupiter Notebook Python

A python program (Using Jupyter Notebook) that implements Gradient Descent to a Neural Network to find the best boundary with the lowest error.

In this notebook, we want to create a machine learning model to accurately predict whether patients have a database of diabetes or not.

The notebooks I worked on during the Numerical Computing course, covering topics such as SVD, nonlinear equations, LSQ, polynomial regression, unconstrained optimization and image enhancement.

This notebook is about data visualization, pre-processing the data and selecting regression model out of different regression model based on the accuracy given on validation data.

The most basic concept of how neural network works. In this notebook I have implemented the neural network to see how the and gate is implemented using neural networks.

"Linear Regression Step by Step" is a repository that provides a comprehensive notebook with step-by-step examples, exercises and libraries to understand and implement Linear Regression easily.