Neural networks for beginners from scatch in tensorflow

Dan We, Anything is possible

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19 Lessons (2h 42m)
    • 1. 1 Introduction to the course

      1:56
    • 2. 2 Understand the relevant steps to build your first neural network from scratch

      10:20
    • 3. 3 What are tensors

      3:31
    • 4. 4 Intro to Tensorflow datatypes

      6:35
    • 5. 5 Tensorflow datatypes and operations

      9:50
    • 6. 6 Tensorflow datatypes variables

      8:06
    • 7. 7 How does the network learn what does loss mean

      14:25
    • 8. 8 How optimization works finishing with the basics

      9:48
    • 9. 9 What is activation

      2:32
    • 10. 10 What is one hot encoding

      1:40
    • 11. 11 Creating the neural network understanding the dataset

      6:04
    • 12. 12 Start building the network 1

      15:20
    • 13. 13 Start building the network 2 shuffle train test and datashapes

      5:44
    • 14. 14 Start building the network 3 hyperparameters

      11:27
    • 15. 15 Start building the network 4 defining the structure

      17:23
    • 16. 16 start buidling the network 5 6

      21:09
    • 17. 17 Start building the network 7 finishing

      7:15
    • 18. 18 Start building the network 8 corrections and running

      6:28
    • 19. 19 Log out final words and important clues

      2:31

About This Class

AI, Artificial Intelligence and neural networks are buzz words. But how do neural networks work. How do they learn. What is machine learning?

How to start with neural networks?

All these questions are addressed in this course to help you get started with artificial intelligence, machine learning and neural networks

We learn the basic conceps, e.g. what is a tensor, how does tensorflow work and how to build a neural network in python from scratch.