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What Makes a Good Book?
Generate features from text and numeric variables to predict the popularity of books.
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Project Description
Extracting value from a variety of data formats is a crucial skill for data scientists to maximize the performance of their machine learning models.
Your expertise has been requested to help an online bookstore in predicting what books will be popular! You'll apply skills across the machine learning workflow, performing EDA, converting data types, transforming features, manipulating data, and tuning a model to maximize its accuracy in predicting popular books.
Project Tasks
- 1Build a book popularity prediction model.
Technologies
Python
Topics
Machine LearningPrerequisites
Feature Engineering for Machine Learning in PythonFrancesca Donadoni
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AI Curriculum Manager at DataCamp
Francesca is an AI Curriculum Manager at DataCamp, where she works to create courses, content, and solutions for AI learning. She has a keen interest in inclusive and accessible AI-based technologies.
After graduating from Imperial College London in 2014, she earned a master's and PhD in Bioengineering at UCL. She spent two years at Northwell Health Labs in the US developing algorithms with clinical data, then returned to London to work as a Machine Learning and AI Engineer with startups before joining DataCamp.