Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
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.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.
In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.
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 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 resume parser example we use the popular Spacy NLP python library for OCR and text classification.