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 deep learning project, you will build a classification system where to precisely identify human fitness activities.
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.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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.
Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.
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, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.