Python notebooks for my graduate class on Detection, Estimation, and Learning. Intended for in-class demonstration. Notebooks illustrate a variety of concepts, from hypothesis testing to estimation to image denoising to Kalman filtering. Feel free to use or modify for your instruction or self-study.

R Markdown Notebook- Data Analysis and Regression Models in R

This repository contains notebook for Predictive Programmer Post

If you liked my analysis, pls upvote my notebook!

If you liked my analysis, pls upvote my notebook!

Jupyter notebook that outlines the process of creating a machine learning predictive model. Predicts the peak "Wins Shared" by the current draft prospects based on numerous features such as college stats, projected draft pick, physical profile and age. I try out multiple models and pick the best performing one for the data from my judgement.

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

Notebook that predicts the rate of the book from using different machine learning models.

Explore ML mini-projects with Jupyter notebooks. Discover predictive analysis for commercial sales, leveraging regression models such as linear regression, decision trees, random forests, lasso, ridge, and extra-trees regressor.

This repository was made with the intention to practice Machine Learning concepts using Jupyter Notebook.

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.

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

This is a simple jupyter notebook for stock price prediction. As a model I've used the linear, ridge and lasso model.

Regression Machine Learning Project

This project involves the prediction of diabetes progression using Ridge Regression in Jupyter Notebook. The dataset contains features such as glucose level, blood pressure, body mass index, and more. Through this analysis, we aim to build a regression model that accurately predicts the progression of diabetes based on the given input features.

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.

Jupyter notebook using machine learning techniques to explore the complex drivers of modern slavery. Models from a research paper are replicated and evaluated . Actions also include filling missing data, training regression models, and analyzing feature importance.