Using this Kaggle dataset, you will explore which type of employees make less or more money, or which employees get normal pay hikes and promotions.

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 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.

Learn to classify the sentiment of sentences from the Rotten Tomatoes dataset. You will be asked to label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive.

Machine Learning Project in R -Predict which customers will leave an insurance company in the next 12 months.

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 - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.

In this project, we will build a model to predict the purchase amount of customers against various products which will help a retail company to create personalized offer for customers against different products.

In this project, we are going to predict how capable each applicant is repaying a loan.

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 machine learning project, we will use hundreds of anonymized features to predict if customers are satisfied or dissatisfied for one of the biggest banks - Santander

In this machine learning project, you will build predictive models to identify wine preferences of people using physiochemical properties of wines and help restaurants recommend the right quality of wine to a customer.

In this deep learning project, you will build a classification system where to precisely identify human fitness activities.

In this project, we are going to work on Deep Learning using H2O to predict Census income.

In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset​ using Keras in Python.

In this data science project, we are going to work on video recognization data and a robust level of image recognization MNIST data.

In this neural network project, we are going to develop an algorithm that will automatically identify the boundaries of the car images which will help to remove the photo studio background.

Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

The goal of this tensorflow project is to identify hand-written digits using a trained model using the MNIST dataset. The MNIST dataset contains a large number of hand written digits and corresponding label (correct digit)

In this tensorlfow project, our goal is to correctly identify digits from a dataset of tens of thousands of handwritten images.

In this data science project, we are going to work on video recognization data and a robust level of image recognization MNIST data.

Deep Learning Project- Learn about implementation of a machine learning algorithm using autoencoders for anomaly detection.

In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.

In this project, we are going to work on Deep Learning using H2O to predict Census income.

In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.

The goal of this IoT project is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice architecture. 

In this deep learning project, we are going to predict which team will win the NCAA basketball tournament of coming 2017 based on past historical data.

In this deep learning project, you will build a classification system where to precisely identify human fitness activities.

In this deep learning project, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.

The goal of this NLP project is to predict which of the provided quora question pairs contain two questions with the same meaning.

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.