In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.
In this project you will use Python to implement various machine learning methods( RNN, LSTM, GRU) for fake news classification.
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.
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.
In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
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.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.