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1
Intro
2
Data Science Process
3
Modeling and Operations
4
Data Science in the Cloud
5
Machine Learning Pipeline
6
Machine Learning Services
7
Choosing an Environment
8
Dashboard
9
Python
10
Training
11
Making it work
12
Training a neural network
13
Changing parameters
14
Machine learning workspace
15
Compute targets
16
Final remarks
17
Question time
Description:
Explore the end-to-end Machine Learning pipeline in the cloud through this 37-minute conference talk. Delve into the multifaceted data science process, covering topics such as modeling, operations, and cloud-based data science. Learn about Machine Learning services, environment selection, and working with Python. Discover how to train neural networks, adjust parameters, and utilize machine learning workspaces and compute targets. Gain insights into creating effective dashboards and implementing practical solutions for data science in cloud environments.

Practicing Data Science in the Cloud

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