In this project, we are going to work on Deep Learning using H2O to predict Census income.
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.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
Deep Learning Project- Learn about implementation of a machine learning algorithm using autoencoders for anomaly detection.
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 H2O and functionality in terms of building Machine Learning models.
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.
Data science project in R to develop automated methods for predicting the cost and severity of insurance claims.
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.