This repository contains my practice of Introduction to Computer Vision and Image Processing lab notebooks.

This project is designed for personal learning and exploration of fundamental machine learning concepts.

This repository is made following the course by Sir Jose Portilla, and focuses on Supervised Machine Learning algorithms. I studied all these concepts in December 2023

Collection of supervised machine learning notebooks

My notebooks when i was learning Machine Learning with scikit-learn.

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

Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.

The notebook provides a step-by-step guide to preparing and analyzing geospatial data and creating a target map using supervised ml techniques.

Notebook used to evaluate various machine learning models used to predict white wine quality.

Notebooks con ejercicios y ejemplos del libro Hands on Machine Learning with scikit-learn and tensorflow 2

This repository contains a Jupyter Notebook that compares the performance of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) architectures for image classification tasks using the Fashion MNIST dataset. The notebook explores the process of training CNN and RNN models

Predicting if a customer will default the next credit card payment using supervised machine learning. Python jupyter notebook attached.

An analysis of potential charity donors using Python Jupyter Notebook. Features cleaning of data, exploration, supervised machine learning and insights.

these are my projects that i submitted for AIML course with great lakes & some good notebooks with great explaination of the topics

A coursework-based repository under the guidance of Prof. Ratnakar Dash, focusing on implementing machine learning algorithms, data preprocessing, model evaluation, and hyperparameter tuning. Includes Jupyter notebooks with hands-on experiments.

This repo houses all my notes, labs and notebooks I used/ created while learning Machine Learning. Following on from this repository I also have a repo for all things Deep Learning too.

Project using machine learning to predict if water wells in Tanzania are functional, non functional, or in need of repair. Written with python using jupyter notebook for the main project flow/analysis and some visual studio code.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

A collection of machine learning mini-projects and analyses developed using Jupyter Notebook. Each project demonstrates practical applications of machine learning algorithms on a variety of datasets, covering techniques from exploratory data analysis (EDA) to model training and evaluation.

In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using Python, and Azure Notebooks.