From the course: Python for AI Projects: From Data Exploration to Impact
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Data exploration - Python Tutorial
From the course: Python for AI Projects: From Data Exploration to Impact
Data exploration
- [Instructor] Now that we've had a taste of natural language processing, we're ready to dive into supervised machine learning, using a real world product recommendation problem, from our Explore California case study. Explore California is an online travel business that offers curated tours across the state, from coastal road trips to wine country retreats. In this section, we'll work with tour purchase data and user attributes to help us build smarter AI powered recommendation systems. We'll begin by loading in our Explore California data sets, which include a list of tour products, sales data, showing which users purchased which tours, and a set of binary user attributes, things like loves hiking or interested in family activities. Once the data is loaded, we'll take our time to understand its structure by reviewing a few sample rows to get a sense of the inputs we'll be working with. We'll also inspect the shape of our data…
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Data exploration4m 56s
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Preparing Customer Data for Predictions for Machine Learning5m 47s
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Training data pipeline6m 46s
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Building Classification Pipelines in Python7m 47s
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Model fitting7m 14s
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Model metrics5m 39s
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Training Purchase Prediction Models6m 58s
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