![]() ![]() ![]() To practice with this type of project, novice machine learning engineers use a dataset that contains fitness activity records for a few people (the more, the better) that was collected through mobile devices equipped with inertial sensors. Many of today's mobile devices are designed to automatically detect when we are engaging in a specific activity, such as running or cycling. Human Activity Recognition with Smartphones To get started, download a stock market dataset from Quantopian or Quandl. It's a great way to become familiar with creating predictions based on massive datasets. Beginners can start small with a project like this and use stock-market datasets to create predictions over the next few months. ![]() Similar to sales forecasting, stock price predictions are based on datasets from past prices, volatility indices, and fundamental indicators. The goal with a project of this scope is to make better data-driven decisions in channel optimization and inventory planning. For example, Walmart provides datasets for 98 products across 45 outlets so developers can access information on weekly sales by locations and departments. While predicting future sales accurately may not be possible, businesses can come close to machine learning. With TensorFlow, they can use the library to create data flow graphs, projects using Java, and an array of applications. This open-source artificial intelligence library is an excellent place for beginners to improve their machine learning skills. Generated by more than 6,000 users, Movielens currently includes more than 1 million movie ratings of 3,900 films. New programmers can practice by coding in either Python or R languages and with data from the Movielens Dataset. This is done through machine learning and can be a fun and easy project for beginners to take on. While figuring out what to stream next can be daunting, recommendations are often made based on a viewer’s history and preferences. Movie Recommendations with Movielens DatasetĪlmost everyone today uses technology to stream movies and television shows. ![]()
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