In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
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.
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
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.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.
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 project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.