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.
In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.
In this deep learning project, you will find similar images (lookalikes) using deep learning and locality sensitive hashing to find customers who are most likely to click on an ad.
In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.
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.
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.
Music Recommendation Project using Machine Learning - Use the KKBox dataset to predict the chances of a user listening to a song again after their very first noticeable listening event.
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.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.