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Whether you shop from meticulously planned grocery lists or let whimsy guide your grazing, our unique food rituals define who we are. Instacart, a grocery ordering and delivery app aim to make it easy to fill your refrigerator and pantry with your personal favorites and staples when you need them. After selecting products through the Instacart app, personal shoppers review your order and do the in-store shopping and delivery for you.
Instacart’s data science team plays a big part in providing this delightful shopping experience. Currently, they use transactional data to develop models that predict which products a user will buy again, try for the first time, or add to their cart next during a session. Recently, Instacart open-sourced this data - see their blog post on 3 Million Instacart Orders, Open Sourced.
In this data science project, we are going to use this anonymized data on customer orders over time to predict which previously purchased products will be in a user’s next order.
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 project, we will try to predict how often players playing a video game called PUBG will win when they play by themselves.
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.