This repository consist of machine learning models which can be use for predicting the future instance. More specifically this repository is a Machine Learning course for those who are interested in learning the basics of machine learning algorithms.

Generate synthetic drilling data that can be used for testing machine learning (ML) models.

Experience a comprehensive exploration of Spotify's musical landscape seamlessly transitioned from Tableau visualizations to SQL analysis. Dive into track inventory, streaming metrics, and sonic trends via interactive dashboards, while leveraging SQL queries for deeper insights into KPIs and cross-platform rankings.

This repository contains ML model for outlier detection

App to guide visually impaired people through mobile and ML models

Classification and regression models for predicting the level of risk associated with extending credit to a borrower and the basic EPS amount respectively.

Vignettes, use cases, toolbox, and datasets to help me when I code in Python.

This project aims to redefine content discovery by delivering personalized article recommendations tailored to individual user preferences. We use advanced machine learning techniques like PCA and K-means clustering to analyze user behavior and article characteristics to provide highly accurate recommendations.

🤗 Push your spaCy pipelines to the Hugging Face Hub

This project aims to forecast inflation rates using machine learning techniques. Leveraging historical economic data on GDP and unemployment rates, the model provides predictions for future inflation trends.

This repository contains an Inflation Predictor ML Project using Flask. The project aims to predict the inflation rate based on economic indicators such as GDP and the unemployment rate.

All weekly exercises in the Spring course Big Data Processes

This is an example Convolutional Neural Network ML model as a solution for various Classification use cases!

This is a simple machine learning project using classifiers for predicting factors which affect student grades, using data from CSV file

This project demonstrates the application of machine learning techniques to predict house prices based on various features. By analyzing the dataset, preprocessing the data, and selecting an appropriate model, we were able to achieve a high level of accuracy in predicting house prices. The trained model can be further refined and deployed.