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TF Machine Learning for Programmers (TensorFlow @ O’Reilly AI Conference, San Francisco ’18)



TensorFlow

In this talk, Laurence Moroney from Google talked about Machine Learning, AI, Deep Learning and more, and how they fit the programmers toolkit. He introduced what it’s all about, cutting through the hype, to show the opportunities that are available in Machine Learning. He also introduced TensorFlow, and how it’s a framework that’s designed to make Machine Learning easy and accessible, and how intelligent apps that use ML can run in a variety of places including mobile, web and IoT.

More TensorFlow videos at O’Reilly AI Conference SF → http://bit.ly/2SjsvZN
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16 thoughts on “TF Machine Learning for Programmers (TensorFlow @ O’Reilly AI Conference, San Francisco ’18)
  1. Really nice job of presenting that, very easy and interesting to follow! What are the chances we could get a video showing how we can use a Regression model outside of our original train and test data? For example with the 70's Housing Price lab, if I had the data from a single house that I wanted to make a prediction on after I had already trained/tested the model. (If it isn't already out there and I've just missed it!)

  2. Very insightful presentation, congrats Lawrence. Quick question: on the Fashion MNIST example, can you comment on what is the rationale for 128 in the second layer? (I got the 28 on the first, and the 10 on the third, but unclear on the 128). Thanks & happy new year!

  3. Good one!
    a quick question @Laurence, when I tried to run your first example and predict (print(model.predict([10]))
    getting following error…
    if len(array.shape) == 1:

    AttributeError: 'int' object has no attribute 'shape'

    Note: tried to run this script in spyder in Anaconda distro.

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