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

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

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

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.

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

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

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 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.

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

Previsão de vendas de uma rede de farmácias.

Global video game sales prediction from year 2008 to 2014 approximately using linear regression and decision tree regression with manipulating min_sample_split hyperparameter to achieve higher accuracy /lower overfitting

Data Science project on Cab Fare Prediction, Machine learning algorithms are used to develop a regression model. Problem Statement : The project is about a cab company who has done its pilot project and now they are looking to predict the fare for their future transactional cases. As, nowadays there are number of cab companies like Uber, Ola, Me…

This project is a study that performs statistical regression analysis for a car buying, selling, and rental company and predicts the total revenue using multiple linear regression based on the analysis

prettyglm provides a set of functions which can easily create beautiful coefficient summaries which can readily be shared and explained.