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 uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.
In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.
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, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
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.
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.
Given big data at taxi service (ride-hailing) i.e. OLA, you will learn multi-step time series forecasting and clustering with Mini-Batch K-means Algorithm on geospatial data to predict future ride requests for a particular region at a given time.
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.
Deep Learning Project to implement an Abstractive Text Summarizer using Google's Transformers-BART Model to generate news article headlines.