Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
Deep Learning Project- Learn about implementation of a machine learning algorithm using autoencoders for anomaly detection.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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.
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.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.