Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
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 machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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.
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.
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 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.