Udemy - A Complete Guide on TensorFlow 2.0 using Keras API [Desire Course]

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[DesireCourse.Net] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API 0. Websites you may like
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1. Introduction
  • 1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 (146.3 MB)
  • 1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..srt (26.4 KB)
  • 2. Course Curriculum & Colab Toolkit.html (0.5 KB)
  • 3. BONUS 10 advantages of TensorFlow.html (0.6 KB)
  • 4. BONUS Learning Path.html (1.4 KB)
10. Dataset Preprocessing with TensorFlow Transform (TFT)
  • 1. Project Setup.mp4 (10.1 MB)
  • 1. Project Setup.srt (2.8 KB)
  • 1.1 Google Colab TFT.html (0.1 KB)
  • 1.2 pollution_small.csv (72.7 KB)
  • 2. Initial dataset preprocessing.mp4 (35.0 MB)
  • 2. Initial dataset preprocessing.srt (8.4 KB)
  • 3. Dataset metadata.mp4 (20.9 MB)
  • 3. Dataset metadata.srt (4.8 KB)
  • 4. Preprocessing function.mp4 (21.1 MB)
  • 4. Preprocessing function.srt (6.0 KB)
  • 5. Dataset preprocessing pipeline.mp4 (74.0 MB)
  • 5. Dataset preprocessing pipeline.srt (10.6 KB)
  • 6. What's next.html (2.1 KB)
11. Fashion API with Flask and TensorFlow 2.0
  • 1. Project Setup.mp4 (36.7 MB)
  • 1. Project Setup.srt (7.7 KB)
  • 1.1 Flask API.zip (372.4 KB)
  • 2. Importing project dependencies.mp4 (11.9 MB)
  • 2. Importing project dependencies.srt (2.5 KB)
  • 3. Loading a pre-trained model.mp4 (20.5 MB)
  • 3. Loading a pre-trained model.srt (3.9 KB)
  • 4. Defining the Flask application.mp4 (12.4 MB)
  • 4. Defining the Flask application.srt (1.8 KB)
  • 5. Creating classify function.mp4 (53.1 MB)
  • 5. Creating classify function.srt (5.6 KB)
  • 6. Starting the Flask application.mp4 (27.6 MB)
  • 6. Starting the Flask application.srt (2.7 KB)
  • 7. Sending API requests over internet to the model.mp4 (35.0 MB)
  • 7. Sending API requests over internet to the model.srt (4.5 KB)
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12. Image Classification API with TensorFlow Serving
  • 1. What is the TensorFlow Serving.mp4 (24.5 MB)
  • 1. What is the TensorFlow Serving.srt (7.6 KB)
  • 10. Sending the POST request to a specific model.mp4 (9.6 MB)
  • 10. Sending the POST request to a specific model.srt (2.4 KB)
  • 2. TensorFlow Serving architecture.mp4 (19.5 MB)
  • 2. TensorFlow Serving architecture.srt (4.5 KB)
  • 3. Project setup.mp4 (25.5 MB)
  • 3. Project setup.srt (4.6 KB)
  • 3.1 Google Colab TensorFlow Serving.html (0.1 KB)
  • 4. Dataset preprocessing.mp4 (23.7 MB)
  • 4. Dataset preprocessing.srt (5.1 KB)
  • 5. Defining, training and evaluating a model.mp4 (23.3 MB)
  • 5. Defining, training and evaluating a model.srt (3.4 KB)
  • 6. Saving the model for production.mp4 (25.4 MB)
  • 6. Saving the model for production.srt (5.3 KB)
  • 7. Serving the TensorFlow 2.0 Model.mp4 (27.9 MB)
  • 7. Serving the TensorFlow 2.0 Model.srt (4.9 KB)
  • 8. Creating a JSON object.mp4 (23.6 MB)
  • 8. Creating a JSON object.srt (3.5 KB)
  • 9. Sending the first POST request to the model.mp4 (27.3 MB)
  • 9. Sending the first POST request to the model.srt (7.1 KB)
13. TensorFlow Lite Prepare a model for a mobile device
  • 1. What is the TensorFlow Lite.mp4 (14.0 MB)
  • 1. What is the TensorFlow Lite.srt (5.2 KB)
  • 10. What's next.html (2.2 KB)
  • 2. Project setup.mp4 (8.0 MB)
  • 2. Project setup.srt (2.6 KB)
  • 2.1 Google Colab TensorFlow Lite.html (0.1 KB)
  • 3. Dataset preprocessing.mp4 (28.8 MB)
  • 3. Dataset preprocessing.srt (4.2 KB)
  • 4. Building a model.mp4 (14.8 MB)
  • 4. Building a model.srt (3.2 KB)
  • 5. Training, evaluating the model.mp4 (15.2 MB)
  • 5. Training, evaluating the model.srt (2.5 KB)
  • 6. Saving the model.mp4 (9.4 MB)
  • 6. Saving the model.srt (2.1 KB)
  • 7. TensorFlow Lite Converter.mp4 (6.3 MB)
  • 7. TensorFlow Lite Converter.srt (1.8 KB)
  • 8. Converting the model to a TensorFlow Lite model.mp4 (4.9 MB)
  • 8. Converting the model to a TensorFlow Lite model.srt (1.4 KB)
  • 9. Saving the converted model.mp4 (8.7 MB)
  • 9. Saving the converted model.srt (1.9 KB)
14. Distributed Training with TensorFlow 2.0
  • 1. What is the Distributed Training.mp4 (11.1 MB)
  • 1. What is the Distributed Training.srt (4.3 KB)
  • 2. Project Setup.mp4 (9.1 MB)
  • 2. Project Setup.srt (2.0 KB)
  • 2.1 Google Colab Distributed Training.html (0.1 KB)
  • 3. Dataset preprocessing.mp4 (25.6 MB)
  • 3. Dataset preprocessing.srt (5.5 KB)
  • 4. Defining a non-distributed model (normal CNN model).mp4 (14.0 MB)
  • 4. Defining a non-distributed model (normal CNN model).srt (3.7 KB)
  • 5. Setting up a distributed strategy.mp4 (7.4 MB)
  • 5. Setting up a distributed strategy.srt (2.3 KB)
  • 6. Defining a distributed model.mp4 (12.5 MB)
  • 6. Defining a distributed model.srt (2.4 KB)
  • 7. Final evaluation - Speed test normal model vs distributed model.mp4 (28.4 MB)
  • 7. Final evaluation - Speed test normal model vs distributed model.srt (4.4 KB)
15. Annex 1 - Artificial Neural Networks Theory
  • 1. Plan of Attack.mp4 (11.8 MB)
  • 1. Plan of Attack.srt (4.0 KB)
  • 2. The Neuron.mp4 (98.7 MB)
  • 2. The Neuron.srt (25.0 KB)
  • 3. The Activation Function.mp4 (45.3 MB)
  • 3. The Activation Function.srt (12.0 KB)
  • 4. How do Neural Networks Work.mp4 (81.8 MB)
  • 4. How do Neural Networks Work.srt (19.0 KB)
  • 5. How do Neural Networks Learn.mp4 (112.2 MB)
  • 5. How do Neural Networks Learn.srt (19.2 KB)
  • 6. Gradient Descent.mp4 (60.6 MB)

  • Description

    A Complete Guide on TensorFlow 2.0 using Keras API

    Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0

    Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, Luka Anicin
    Last updated 8/2020
    English
    English [Auto-generated]

    For More Courses Visit: https://desirecourse.net



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Udemy - A Complete Guide on TensorFlow 2.0 using Keras API [Desire Course]

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5.1 GB
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Udemy - A Complete Guide on TensorFlow 2.0 using Keras API [Desire Course]

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