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O’reilly – Advanced Machine Learning with Hilary Mason

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O'reilly - Advanced Machine Learning with Hilary Mason
English | Audio: aac, 44100 Hz, stereo | Video: h264, yuv420p, 1280x720, 25.00 fps(r) | 1.26GB
Genre: E-learning

In this sequel to An Introduction to Machine Learning with Web Data, bit.ly lead scientist Hilary Mason shows you how to solve real-world problems with machine learning. Using real data from an actual ecommerce website, you will apply production quality algorithms to understand all the issues that arise when working in a live environment.

Learn how to apply best practices to common types of machine learning problems, extract quantifiable data, and explore several open source tools and how to use them.

Segments include:
Introduction: Discover what the course covers, and what you'll learn.
Classification Part 1: Techniques and best practices to learn from your data.
Classification Part 2: Learning which attributes maximize desired behavior.
Clustering: How to explore and visualize unstructured data when your data is a mess and there's no known structure.
Learning from data: Best practices for offline vs stream analysis.
Conclusions: Asking the right questions is hard. Once you've formulated the question you'll know whether your task is easy or hard

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  1. O’reilly – 与Hilary Mason一起学高级机器学习 本教程是机器学习Web数据导论的后续部分,由Hilary Mason讲授如何利用机器学习解决真正工作中的问题。利用真实电子商务网站的真正数据,你将应用产品质量算法解决所有这些真实环境中所发生的问题。 通过教程的学习,掌握如何应用最佳时间处理机器学习中常见的问题,提取量化数据以及利用几款开源工具的使用。
    wilde(特殊组-翻译)2年前 (2015-01-05)