Introduction to Deep Learning Course
Course Description
In this one-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.
Schedule
- 09:00-10:05 | 01: Introduction to Deep Learning
- 10:05-10:15 | Break
- 10:20-12:00 | 02: Neural Networks
- 12:00-13:00 | Lunch
- 13:00-13:45 | 03: Classification and Convolutional Neural Networks
- 13:45-13:50 | Short break
- 13:50-15:15 | 04: Refining the model
- 15:15-15:30 | Break
- 15:30-17:00
- 05: Deployment & Transfer Learning
- 06: DL in other fields & Wrapup
Overview
01: Introduction to Deep Learning
Lab 01: Introduction to Tensorflow Keras
02: Neural networks
Lab 02: Classifying images of clothing
03: Classification and Convolutional Neural Networks
Lab 03: Image classification with CNNs
04: Refining the model
Lab 04: Dogs & Cats with data augmentation
4a Without Data augmentation
4b With Data augmentation
05: Deployment & Transfer Learning
Lab 05: Saving and Loading models
Lab 06: Tensorflow hub and Transfer learning
06: DL in other fields
Lab 07: Final exercise, flowers with data augmentation
Extra Lab 02: Handwritten digits generation with DCGAN