Project that demonstrates data analytics and visualization along with showing past trends and predicting future trends with ML.

python module for wild cluster bootstrapping

In-depth exploration of linear regression models, including data cleaning, model building, and performance evaluation on various datasets.

Machine Learning Notebooks for various Algorithms with data file

This repository offers a collection of basic hands-on machine learning concepts taken from deeplearning.AI course by Andrew Ng

Implementation of different machine learning models

This model utilizes regression models and accurately predicts employee salaries based on experience, previous CTC, and job roles, promoting fair salary structures and optimizing resource allocation for streamlined HR operations.

This repository contains a Jupyter notebook that implements and optimizes several machine learning models on a dataset

Repository related to courses and submission from kaggle

🌈📊📈 The Zillow Home Value Prediction project employs linear regression models on Kaggle datasets to forecast house prices. 📉💰Using Apache Spark (PySpark) within a Docker setup enables efficient data preprocessing, exploration, analysis, visualization, and model building with distributed computing for parallel computation.

All my learnings from "Machine Learning with Python" course offered by "IBM" on Coursera are reflected here.

Github repo for my in-progress book, "Visualizing Multivariate Data and Models in R"

This project will cover some of the basic Artificial Intelligence along the course using Python. Mainly will use Numpy to build everything. I write all the files in Python and it refers back to the school labs at Dalhousie University.

This repo contains various Regression Models

The lingress project is to develop the pipeline to analyse the Nuclear magnetic resonance (NMR) dataset using a univariate linear regression model. This package contains the analysis with linear regression (OLS) and visualises the interpretation of the results with a p-value of all NMR peaks.

Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.

This repository contains a machine learning project for predicting house prices using various regression models, including Linear Regression, Random Forest Regressor, and XGBoost Regressor. The project involves data pre-processing, feature engineering, model training, and evaluation.

Implementing linear regression using sckit-learn

Applying feature scaling with linear regression in python