6.6: TensorFlow.js: Layers API Part 2 – Intelligence and Learning

[ad_1]
In part 2 of the TensorFlow.js Layers API (“tf.layers”), I train a model to predict an output. (Note the data here is made up and meaningless.)

🔗 TensorFlow.js:
🔗 ml5:

🎥 My Neural Networks playlist:
🎥 Mathematics of Gradient Descent:
🎥 ES6 Promises:
🎥 async/await:

🚂 Website:
💖 Patreon:
Store:
📚 Book recommendations:

💻

🎥 For More Intelligence and Learning videos:
🎥 For More Coding Challenges:

🔗
🔗


Posted

in

by

Tags:

Comments

10 responses to “6.6: TensorFlow.js: Layers API Part 2 – Intelligence and Learning”

  1. Vonexya Avatar

    Aren't you get bored ? Coding coding and coding again

  2. Alif Arya Wiranda Avatar

    very good explanation sir… i am waiting for Fat predict example using tensorflow.js. how we can add the label inside the training data .

  3. Adham Aly Avatar

    Thanks for your videos!!

  4. unicornFairy with password protected vegina Avatar

    let me tell you what happened in your life…… you have been enlightened my friend. proof => you're using Atom :')

  5. Colin Paddock Avatar

    So is gradient descent essentially the same as a hill climbing algorithm? With the stochastic element to avoid entrapment in local optima?

  6. Shanzid Shaiham Avatar

    You've changed my life..
    I've been following you for over a year now and ever since the beginning you've managed to teach me such complex topics with such finesse and I've managed to pick up most of what you teach. You've shown me that ML is a very interesting topic and anyone could do it without having to read through thousands of research papers. Thank you so much.

  7. Alessandro Astone Avatar

    Aren't there performance implications of running fit in a loop, instead of just specifying the number of epochs in config?

  8. The Riptide Raptor Avatar

    2 Layers videos, nice

Leave a Reply

Your email address will not be published. Required fields are marked *