Project 1: Predict the median value of owner-occupied homes. (Boston Dataset)
Description: - This is a popular dataset used in pattern recognition literature. The data set comes from the real estate industry in Boston (US). This is a regression problem. The data has 506 rows and 14 columns. Thus, it’s a fairly small data set where you can attempt any technique without worrying about your laptop’s memory being overused.
Project 2: Predict the sales of a store. (Bigmart sales dataset)
Description: - Retail is another industry which extensively uses analytics to optimize business processes. Tasks like product placement, inventory management, customized offers, product bundling, etc. are being smartly handled using data science techniques. As the name suggests, this data comprises of transaction records of a sales store. This is a regression problem. The data has 8523 rows of 12 variables.
Project 3:Predict the handwritten digits. (MNIST dataset)
Description: - MNIST is dataset consisting of handwritten digits. We will use some algorithm to predict those digits. There are total 70000 values, among which 60000 are for train and 10000 for test set.
Project 4:Recommend new movies to users. (Movie lens dataset)
Description: - Have you built a recommendation system yet? Here’s your chance! This dataset is one of the most popular & quoted datasets in the data science industry. It is available in various dimensions. We will use a dataset with 1 million ratings from 6,000 users on 4,000 movies.
And many more