<p>The typical data science task in industry starts with an βaskβ from the business. But few data scientists have been taught what to do with that ask. This book shows them how to assess it in the context of the businessβs goals, reframe it to work optimally for both the data scientist and the emplo
Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications
β Scribed by Andrew Kelleher; Adam Kelleher
- Publisher
- Addison-Wesley
- Year
- 2019
- Tongue
- English
- Leaves
- 274
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Part I
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Part II
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Chapter 14
Part III
Chapter 15
Chapter 16
Chapter 17
Chapter 18
Chapter 19
π SIMILAR VOLUMES
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<p><span>The confluence of big data, artificial intelligence (AI), and machine learning (ML) has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from divers
<span>MACHINE LEARNING AND DATA SCIENCE</span><p><span>Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.</span></p><p><span>Machine
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