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.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
In this project, we are going to work on Deep Learning using H2O to predict Census income.
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 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.
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 predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset using Keras in Python.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
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.