Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
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 machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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.
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.
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.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
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, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.