In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
In this machine learning project, you will use the video clip of an IPL match played between CSK and RCB to forecast key performance indicators like the number of appearances of a brand logo, the frames, and the shortest and longest area percentage in the video.
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.
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 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 data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.
In this deep learning project, you will build your own face recognition system in Python using OpenCV and FaceNet by extracting features from an image of a person's face.
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 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 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.