Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
In this ML Project, you will use the Avocado dataset to build a machine learning model to predict the average price of avocado which is continuous in nature based on region and varieties of avocado.
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, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
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 deep learning project, you will build a convolutional neural network using MNIST dataset for handwritten digit recognition.
In this NLP Project, you will learn how to use the popular topic modelling library Gensim for implementing two state-of-the-art word embedding methods Word2Vec and FastText models.
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 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 project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.