Machine learning-based application for predicting the injury recovery time period a sports person based on injury type and diet plan.

Training of a neural network for nonlinear regression prediction with TensorFlow and Keras API.

Models Supported: VGG11, VGG13, VGG16, VGG16_v2, VGG19 (1D and 2D versions with DEMO for Classification and Regression).

A NOVEL BLIND IMAGE QUALITY ASSESSMENT METHOD BASED ON REFINED NATURAL SCENE STATISTICS

A system and web app to discover good deals of rental properties, built and automated on a serverless architecture.

This project aims to develop a machine learning model that predicts the demand for bike sharing in a given location. By analyzing historical data on weather conditions, day of the week, and other factors, we aim to create a model that can accurately forecast the number of bikes that will be rented at different times.

The objective of this project is to study the COVID-19 outbreak using basic statistical techniques and make short term predictions using ML regression methods.

Detecting the functioning level of a patient from a free-text clinical note in Dutch.

In this project I have implemented 14 different types of regression algorithms including Linear Regression, KNN Regressor, Decision Tree Regressor, RandomForest Regressor, XGBoost, CatBoost., LightGBM, etc. Along with it I have also performed Hyper Paramter Optimization & Cross Validation.

This repo covers the basic machine learning regression projects/problems using various machine learning regression techniques and MLP Neural Network regressor through scikit learn library

This repository documents a complete ML workflow to model Uber fares in Paris, from granular EDA and feature engineering to building and fine-tuning a stacking regressor on 10k real-world rides.

This project focuses on developing a machine learning model to predict the price of diamonds based on various attributes. By analyzing a dataset that includes information about the carat weight, cut, color, clarity, and other factors, we aim to create a model that can accurately estimate the price of diamonds.

Previsão de vendas de uma rede de farmácias.

Machine learning projects to showcase applications of ML in various industries/disciplines/fields

Summer Training on Machine Learning by Internshala, powered by Analytics Vidhya,

Creating an ML model to predict the estimated time of arrival at the dropoff point for a single journey on a ride-hailing app.

This is the experiment code for the publication "Identifying Informative Nodes in Attributed Spatial Sensor Networks using Attention for Symbolic Abstraction in a GNN-based Modeling Approach".

This project uses machine learning to predict the price of a used car. The model is trained on a dataset of historical car sales data, and it can then be used to predict the price of a car based on its features.

EcoSphereAI is a sustainable, AI-driven platform optimizing connectivity systems with features like energy optimization, predictive maintenance, and sustainability reporting. Build the future of efficient and green networks!