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 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 data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
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 machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
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.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.