Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.
There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.
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.
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.
Data Science Project in R-Predict the sales for each department using historical markdown data from the Walmart dataset containing data of 45 Walmart stores.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.