Hilary Mason: An Introduction to Machine Learning with Data Web
[О'Rеilly Media] Hilary Mason: An Introduction to Machine Learning with Data Web
English | Duration: 2h 43m | H264 | 1280x720 | 29.970fps 1200kbps | AAC 44100Hz mono 48kbps | 1.43 GB
Genre: Video Training
Once you've accumulated a pile of data through your web application, what do you do with it? In this insightful video course, bit.ly lead scientist Hilary Mason shows you how to solve data analysis problems using basic machine learning techniques and frameworks. You'll follow several examples through the entire process—from obtaining, cleaning, and exploring data to building a model and interpreting the results.
Examine several real-world analysis solutions, including supervised learning and classification, unsupervised learning and clustering, and building common machine learning applications such as recommendation systems. If you're a developer interested in the math and processes necessary to apply machine learning techniques to web data, this video course is for you.
Intended Audience:
This class is intended for developers who are interested in an introduction to the math and processes to apply machine learning techniques to web data.
Introduction (20 minutes)
Classifying Web Documents - The Theory (29 minutes)
Classifying Web Documents - The Code (47 minutes)
Clustering, Recommendations, and Probability (54 minutes)
Conclusion (11 minutes)