Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
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.
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset using Keras in Python.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
In this project, we are going to work on Deep Learning using H2O to predict Census income.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
Deep Learning Project- Learn about implementation of a machine learning algorithm using autoencoders for anomaly detection.