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


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This course will educate you tips on how to use Keras, a neural community API written in Python and built-in with TensorFlow. We will learn to put together and course of knowledge for synthetic neural networks, construct and practice synthetic neural networks from scratch, construct and practice convolutional neural networks (CNNs), implement effective-tuning and switch studying, and extra!

⭐️🦎 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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Comment List

  • freeCodeCamp.org
    November 9, 2020

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

  • freeCodeCamp.org
    November 9, 2020

    1.25 speed bois

  • freeCodeCamp.org
    November 9, 2020

    So sexy course!

  • freeCodeCamp.org
    November 9, 2020

    Hi, am actually having problem with anaconda installation on my system. i have successfully downloaded the anaconda setup but i get hooked up during installation because i don't know which folder to install it in to. my pc is a 32bit system and am using windows 8 os

  • freeCodeCamp.org
    November 9, 2020

    Running huge blocks of code like 20 lines of imports and 20-30 lines of folder creation was a huge inconvenience for me. Those huge blocks of codes should have been freely available to people watching this video.

  • freeCodeCamp.org
    November 9, 2020

    Nette Edel Pils ist das beste Bier

  • freeCodeCamp.org
    November 9, 2020

    Thanks for the course

  • freeCodeCamp.org
    November 9, 2020

    Hi, Could you provide a turtorial on hyprerparameters tuning using neptune ml and sklearn

  • freeCodeCamp.org
    November 9, 2020

    8/10 would bang

  • freeCodeCamp.org
    November 9, 2020

    nice

  • freeCodeCamp.org
    November 9, 2020

    yes, thank you

  • freeCodeCamp.org
    November 9, 2020

    thank you very much. this course is amazing

  • freeCodeCamp.org
    November 9, 2020

    thankyou verymuch

  • freeCodeCamp.org
    November 9, 2020

    When code gets for money on name membership, why these we need like tutorial,many intellectual persons teaching on YouTube with their free material and datasets

  • freeCodeCamp.org
    November 9, 2020

    Tutorial starting in a room with a bed, Just reminded me Livejasmin in first look!

  • freeCodeCamp.org
    November 9, 2020

    Incredible video! Very well taught with clear explanations for all the different concepts. This has allowed me to put my first foot through the door to understand Keras/TensorFlow!

  • freeCodeCamp.org
    November 9, 2020

    How can we submit a video tutorial? I would like to contribute…

  • freeCodeCamp.org
    November 9, 2020

    Very precise and accurate information
    Thanks for sharing 👍

  • freeCodeCamp.org
    November 9, 2020

    1:16 I am sure I missed something, Still…. Where does that labels come from? ? How did it distinguish cats and dogs?

  • freeCodeCamp.org
    November 9, 2020

    Muchas gracias Miss Mandy….que habitación tan ordenada, saludos de Perú

  • freeCodeCamp.org
    November 9, 2020

    physical_devices=tf.config.experimental.list_physical_devices("GPU")

    print(len(physical_devices))

    This prints 0 for me, im using Lenovo Legion Y540 with GTX 1660Ti

  • freeCodeCamp.org
    November 9, 2020

    If the probability of a given older person experiencing side effects is 95% (respectively younger person not experiencing side effects 95%), I would think that the model's accuracy can not possibly be higher than 95%, is this right?
    Because for a random person picked from the dataset, you can only predict it with 95% certainty. This would reflect the model's accuracy of 94%.

  • freeCodeCamp.org
    November 9, 2020

    Getting Import error for imagenet_utils
    ImportError: cannot import name 'imagenet_utils' from 'tensorflow.keras.applications' (unknown location)
    Any alternative solution ? Is it removed from Tensorflow ? I am using TF2.

  • freeCodeCamp.org
    November 9, 2020

    There is a slight problem in the presentation. You reshaped the scaled_train_samples but there was never any code to do that with train_labels. You must have actually done that before you ran the fit() function or it would have never run but I didn't see anything in the code about it. Once I added train_labels <- train_labels.reshape(-1,1) the fit() function ran successfully.

  • freeCodeCamp.org
    November 9, 2020

    is there any github repo for this code?

  • freeCodeCamp.org
    November 9, 2020
  • freeCodeCamp.org
    November 9, 2020

    i just want to confirm what you mean Green or red mean pixel value from training set i.e average red/green value of each individual image subtracting from that particular image red/green values or taking mean red or green value from of all training images and subtracting it from each images red or green values

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