# Introduction to Deep Learning Course

# Course Description

In this full-day introductory workshop, you’ll learn the basics of deep learning by training and deploying neural networks.

# Learning Outcomes

By the end of this course, participants will be able to:

  • Implement common deep learning workflows using Tensorflow Keras framework.
  • Experiment with data, training parameters, network structure, and other strategies to increase performance and capability.
  • Deploy your neural networks to start solving real-world problems.

# Pre-requisites

  • Basic knowledge of the Python programming language.

# Overview

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# 01: Introduction to Deep Learning

# Lab 01: Introduction to Tensorflow Keras

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# 02: Neural networks

# Lab 02: Classifying images of clothing

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# 03: Classification and Convolutional Neural Networks

# Lab 03: Image classification with CNNs

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# 04: Refining the model

# Lab 04: Dogs & Cats with data augmentation

# 4a Without Data augmentation

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# 4b With Data augmentation

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# 05: Deployment & Transfer Learning

# Lab 05: Tensorflow hub and Transfer learning

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# Lab 06: Saving and Loading models

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# 06: DL in other fields

# Lab 07: Final exercise, flowers with data augmentation

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# Extra Lab 01: Text classification with RNN

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# Extra Lab 02: Handwritten digits generation with DCGAN

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