In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.
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 project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.
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 machine learning churn project, we implement a churn prediction model in python using ensemble 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.
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 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 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 data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.