In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset using Keras in Python.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
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 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.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
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.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.