Deep learning Projects

Notebooks explaining various Machine Learning concepts.

Training Repository for my ML and DL notebooks

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

Two Python notebooks in which Stochastic Gradient Descent and K-means algorithms are run over the Spark framework

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

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

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.

Deep Learning projects

A set of Jupyter notebooks that investigate and compare the performance of several numerical optimization techniques, both unconstrained (univariate search, Powell's method and Gradient Descent (fixed step and optimal step)) and constrained (Exterior Penalty method).

A series of documented Jupyter notebooks implementing polynomial regression models and model performance analysis

Get Started with Deep Learning

Use python Jupyter notebooks (numpy, pandas, matplotlib, etc) to implement and test simple machine learning algorithms.

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

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

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

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