In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
In this data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.
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.
Given big data at taxi service (ride-hailing) i.e. OLA, you will learn multi-step time series forecasting and clustering with Mini-Batch K-means Algorithm on geospatial data to predict future ride requests for a particular region at a given time.
Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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 time series project, you will forecast Walmart sales over time using the powerful, fast, and flexible time series forecasting library Greykite that helps automate time series problems.
In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.