In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical 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.
In this deep learning project, you will learn how to build your custom OCR (optical character recognition) from scratch by using Google Tesseract and YOLO to read the text from any images.
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 Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.
Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.
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.
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.
Classification is one of the basic things in ML and most of us jump to Neural networks or boosting to predict classes. But more often than not, to make the other person understand how the classification is happening, we need to use basic models like Logistic, decision trees etc. In this project we talk about you can apply various basic techniques, the maths and intuition behind them and how they paved way to bagging and boosting of the world