In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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 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.
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.
Data science project in R to develop automated methods for predicting the cost and severity of insurance claims.
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.
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.
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.
There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.