In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.
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.
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
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.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.