Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.
In this machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.
In this project you will use Python to implement various machine learning methods( RNN, LSTM, GRU) for fake news classification.
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.
In this data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.