This course will sell out—sign up today!
Christian Moscardi walks you through developing a machine learning pipeline, from prototyping to production, with the Jupyter platform, exploring data cleaning, feature engineering, model building and evaluation, and deployment in an industry-focused setting. Along the way, you’ll learn Jupyter best practices and the Jupyter settings and libraries that enable great visualizations.
Day 1: Recommendation engine
– Overview of data and its wrangling
– Item-item correlations and finding similar items
– User similarity and predicting user ratings
– Collaborative filtering
– Evaluating model performance
Day 2: Anomaly detection
– Data format and goal
– Limitations of time series data
– Detrending and seasonality
– Windowing and local scores
– Setting thresholds for classification
– Online learning
Christian Moscardi is director of technology for the Data Incubator. Previously, Christian developed a CMS for food blogs, worked for Google, and researched and taught at Columbia. He organizes with BetaNYC, New York’s civic tech organization, and contributes to various civic data projects. His extracurricular activities include cooking, playing the piano, and exploring New York.
Get the Platinum pass to add this course to your package. Early Price ends June 30.
Help us make this conference the best it can be for you. Have questions you'd like this speaker to address? Suggestions for issues that deserve extra attention? Feedback that you'd like to share with the speaker and other attendees?
Join the conversation here (requires login)
©2017, O'Reilly Media, Inc. • (800) 889-8969 or (707) 827-7019 • Monday-Friday 7:30am-5pm PT • All trademarks and registered trademarks appearing on oreilly.com are the property of their respective owners. • email@example.com