In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
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 data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.
Deep Learning Project- Learn about implementation of a machine learning algorithm using autoencoders for anomaly detection.
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.
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.
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 project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset using Keras in Python.
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.