Learning TensorFlow

on YouTube ↗41m

" summary

Overview of TensorFlow basics with code: building Variables, Placeholders, Custom Functions as graph nodes, using a session to run parts of the graph, and converting a Python function to a node via hi_func. Shows an image transpose example, trains linear regression for 1000 iterations and recovers weights ~2.2 and ~5.8, runs a 2000x2000 Game of Life update fully on GPU, and measures CPU vs GPU dot+sum ~12s vs ~1.3s. Also mentions tflearn/keras backends.

AI-written summary · about

" chapters (12)

1. 0:00Introduction
2. 10:20Example Graph
3. 11:10Basic Example
4. 13:06Raw Image Data
5. 14:25Placeholders
6. 16:43Reverse
7. 20:28Variables
8. 23:09Training
9. 26:28Python
10. 27:41Machine Learning
11. 31:43TensorFlow
12. 32:57Questions

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