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

Jupyter notebooks for learning machine learning tools.

Supervised Machine Learning | Neural Network | Jupyter Notebook | Python | Scikit library

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

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

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

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

This repository contains a Jupyter notebook completed as part of the "Python Project for Data Science" module of the IBM Data Science Professional Certificate. In the second notebook, the same stock data is used to make predictions using ML.

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.

A collection of notebooks and scripts covering essential data science concepts. Includes data manipulation, cleaning, analysis, and visualization techniques.

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 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.

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.