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Brief practice Introduction to Keras for image processing


  • Part I: Introducción

    • Basic Variables
    • Basic Operations
  • Part II: Machine Learning

    • Lineal Regression
    • Logistic Regression
    • Neural Networks
  • Part III: Deep Learning for Classification

    • Convolutional Neural Networks
    • CNNs Arquitectures
    • Transfer Learning
    • CNN using custom data
    • Basic RNN (LSTM)
  • Part IV: Deep Learning for Object Detection

    • Faster RCNN using Pre-trained Model
  • Part V: Deep Learning for Pose Estimation

    • Body Estimation using pre-trained model

Note: Use environment.yml to download libraries in order to run every notebook.

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Introduction to Keras applying CNN and RNN

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