Keras with TensorFlow Course – Python Deep Learning and Neural Networks for Beginners Tutorial

///Keras with TensorFlow Course – Python Deep Learning and Neural Networks for Beginners Tutorial

Keras with TensorFlow Course – Python Deep Learning and Neural Networks for Beginners Tutorial

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This course will teach you how to use Keras, a neural network API written in Python and integrated with TensorFlow. We will learn how to prepare and process data for artificial neural networks, build and train artificial neural networks from scratch, build and train convolutional neural networks (CNNs), implement fine-tuning and transfer learning, and more!

⭐️🦎 COURSE CONTENTS 🦎⭐️
⌨️ (00:00:00) Welcome to this course
⌨️ (00:00:16) Keras Course Introduction
⌨️ (00:00:50) Course Prerequisites
⌨️ (00:01:33) DEEPLIZARD Deep Learning Path
⌨️ (00:01:45) Course Resources
⌨️ (00:02:30) About Keras
⌨️ (00:06:41) Keras with TensorFlow – Data Processing for Neural Network Training
⌨️ (00:18:39) Create an Artificial Neural Network with TensorFlow’s Keras API
⌨️ (00:24:36) Train an Artificial Neural Network with TensorFlow’s Keras API
⌨️ (00:30:07) Build a Validation Set With TensorFlow’s Keras API
⌨️ (00:39:28) Neural Network Predictions with TensorFlow’s Keras API
⌨️ (00:47:48) Create a Confusion Matrix for Neural Network Predictions
⌨️ (00:52:29) Save and Load a Model with TensorFlow’s Keras API
⌨️ (01:01:25) Image Preparation for CNNs with TensorFlow’s Keras API
⌨️ (01:19:22) Build and Train a CNN with TensorFlow’s Keras API
⌨️ (01:28:42) CNN Predictions with TensorFlow’s Keras API
⌨️ (01:37:05) Build a Fine-Tuned Neural Network with TensorFlow’s Keras API
⌨️ (01:48:19) Train a Fine-Tuned Neural Network with TensorFlow’s Keras API
⌨️ (01:52:39) Predict with a Fine-Tuned Neural Network with TensorFlow’s Keras API
⌨️ (01:57:50) MobileNet Image Classification with TensorFlow’s Keras API
⌨️ (02:11:18) Process Images for Fine-Tuned MobileNet with TensorFlow’s Keras API
⌨️ (02:24:24) Fine-Tuning MobileNet on Custom Data Set with TensorFlow’s Keras API
⌨️ (02:38:59) Data Augmentation with TensorFlow’ Keras API
⌨️ (02:47:24) Collective Intelligence and the DEEPLIZARD HIVEMIND

⭐️🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎⭐️

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By |2021-01-06T11:41:43+00:00January 6th, 2021|Python Video Tutorials|41 Comments

41 Comments

  1. deeplizard January 6, 2021 at 11:41 am - Reply

    Hi everyone! Hope you all learn and gain from this course! Come check out the other deep learning courses available on our channel! ❤️🦎

  2. Kartik Anand January 6, 2021 at 11:41 am - Reply

    so many fucking ads

  3. james hopkins January 6, 2021 at 11:41 am - Reply

    ssngrpt

  4. William Jimenez January 6, 2021 at 11:41 am - Reply

    :-*

  5. Murlidhar Talwani January 6, 2021 at 11:41 am - Reply

    Amazing Video

  6. Pajeet Singh January 6, 2021 at 11:41 am - Reply

    why do ppl use jupyter?

  7. Miguel Ribeiro January 6, 2021 at 11:41 am - Reply

    How different is Keras vs tf.Keras?

  8. Easy Typing and Translation January 6, 2021 at 11:41 am - Reply

    I am not able to concentrate properly.

  9. adsr January 6, 2021 at 11:41 am - Reply

    the one thin Blockchain technology will change – https://youtu.be/vertTU_7sGI

  10. Maximilian January 6, 2021 at 11:41 am - Reply

    I wonder if anyone here actually tried doing pip install tensorflow.
    Because it's rarely that easy.

  11. Language Tech January 6, 2021 at 11:41 am - Reply

    The efficient way of doing it instead of the expensive loops and in one line:
    np.random.uniform(low=13, high=65, size=(100,)).astype("int32")

  12. Prince Mahin January 6, 2021 at 11:41 am - Reply

    what ever i had crush on her

  13. yz830620 January 6, 2021 at 11:41 am - Reply

    the best video ever, easy to understand. Great thanks!

  14. Kourosh Zarei January 6, 2021 at 11:41 am - Reply

    tf is wrong with this comment section. literally nowhere else on yt do you get this weird tone

  15. X X January 6, 2021 at 11:41 am - Reply

    She likes that mobilenet so bad lol

  16. Diego Matheu January 6, 2021 at 11:41 am - Reply

    so wonderful, hope you guys keep this up to date

  17. Nicklaus Mikaelson January 6, 2021 at 11:41 am - Reply

    Mandyy! You came and you gave without taking!!

  18. Adamya Tripathi January 6, 2021 at 11:41 am - Reply

    Hey @freeCodeCamp.org, I have one heart. How many times you're gonna win it?

  19. C Zheng January 6, 2021 at 11:41 am - Reply

    It deeply bothers me that the overhanging night light behind her to her left is misaligned.

  20. Isaac Nazar January 6, 2021 at 11:41 am - Reply

    I am not a programmer/coder. I found this video very soothing and inspiring simply the vision it infused in creative aspects. I sat 6 years in the hole so the slightest intellectual understanding blows up into wisest yet connected set for output variable. I am a mystic, someone needs to code what I see.

  21. Keith Makan January 6, 2021 at 11:41 am - Reply

    @51:40 lol 420 woohoo

  22. Keith Makan January 6, 2021 at 11:41 am - Reply

    Very good intro example, easy to setup problem can be tweaked to explore more and doesn't require pictures or strange formats and other downloads.

  23. Ragu Raghupathi January 6, 2021 at 11:41 am - Reply

    Executing Line 14 gives an error " sclaed_train_variables is not defined.. What am I doing wrong?

  24. Kaio Andriani January 6, 2021 at 11:41 am - Reply

    Thank you,!!

  25. Konrad Pietras January 6, 2021 at 11:41 am - Reply

    you shouldn't call fit_transform on test_samples in 43:20. You should use the same scaler that was fitted on train_samples.

  26. Rhodium 45 January 6, 2021 at 11:41 am - Reply

    Lol, this video is impossible to learn from. Every 10 minutes I find myself drifting off, daydreaming about the instructor. Gorgeous!

  27. PRADHYUMN SHARMA January 6, 2021 at 11:41 am - Reply

    Lesson 32 : "if she's beautiful and coder"
    Just Marry her

  28. Guillem Perdigó Oliveras January 6, 2021 at 11:41 am - Reply

    Thank you for the video!!

    At 43:06 if the test set should be scaled the same way the train set was, shouldn't we be using scaler.transform (i.e. without fitting the scaler again).

  29. Barah Ah January 6, 2021 at 11:41 am - Reply

    The bad thing about this tutorial is the instructor is not explaining why and what does the important parameters like filters, pool size, strides do. So -1

  30. Michal Ziobro January 6, 2021 at 11:41 am - Reply

    I like this split into episods. As i watch this from time to time and move steady progress

  31. Michal Ziobro January 6, 2021 at 11:41 am - Reply

    I will prefere Keras in Swift not Python

  32. Darkness Evil January 6, 2021 at 11:41 am - Reply

    can you do a segment for.. keras & plaidml but no tensorflow.. becuse im using plainml as backend i dont plan to install ubuntu as dual boot or main one just to have fun with ai.. ngraph-bridge is not available to wsl2 nor windows 🙁 im no expert it seems its needed to make keras -> tensorflow -> ngraph -> plaidml recognize to use my navi10 gpu.. just like mac setup.

  33. L C January 6, 2021 at 11:41 am - Reply

    Most beautifull teacher < 3

  34. Kunal Rai January 6, 2021 at 11:41 am - Reply

    Thank you for the course but what is the benefit

  35. nargonne January 6, 2021 at 11:41 am - Reply

    2:09:10 – Expresso is just the coffee. It becomes a cappuccino when you add milk and foam. If it's getting classified as expresso then I wonder if the original dataset labels were added incorrectly by human editors that didn't know the difference.

  36. Suckefied_Amby January 6, 2021 at 11:41 am - Reply

    at 1:15 when did we associate Labels with Image? we only created the images' batch but when did we associate with its labels?

  37. SÆ¡n January 6, 2021 at 11:41 am - Reply

    From VietNam with loves

  38. mirko perrone January 6, 2021 at 11:41 am - Reply

    I am an Italian guy and that is not an espresso, It is a cappuccino 😀 watching that part of the video was a stab to my heart 😀
    The espresso is the Italian coffee made by the bar espresso coffee machine.

  39. Sanjay Tech World SK Education January 6, 2021 at 11:41 am - Reply

    Well thank you for this video

  40. Lutscherrrr January 6, 2021 at 11:41 am - Reply

    1.25 speed bois

  41. Sergio Morell January 6, 2021 at 11:41 am - Reply

    So sexy course!

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