Tag: GANs

Course content

• Introduction and Outline
• Generative Modeling Review
• Variational Autoencoders
• Generative Adversarial Networks (GANs)
• Theano and Tensorflow Basics Review
• Setting Up Your Environment (FAQ by Student Request)
• Extra Help With Python Coding for Beginners (FAQ by Student Request)
• Effective Learning Strategies for Machine Learning (FAQ by Student Request)
• Appendix / FAQ Finale

Course content

• Introduction
• DCGAN and WGAN
• cGAN – Pix2Pix and CycleGAN
• SRGAN and ESRGAN
• StyleGAN
• VQGAN + CLIP – text to image
• Other types of GANs
• Additional content 1: Artificial neural networks
• Additional content 2: Convolution neural networks
• Final remarks

Course content

• Introduction
• Intro to Computer Vision & Deep Learning
• Installation Guide
• Handwriting Recognition
• OpenCV Tutorial – Learn Classic Computer Vision & Face Detection (OPTIONAL)
• Neural Networks Explained
• Convolutional Neural Networks (CNNs) Explained
• Build CNNs in Python using Keras
• What CNNs ‘see’ – Filter Visualizations, Heatmaps and Salience Maps
• Data Augmentation: Cats vs Dogs
• Assessing Model Performance
• Optimizers, Learning Rates & Callbacks with Fruit Classification
• Batch Normalization & LeNet, AlexNet: Clothing Classifier
• Advanced Image Classiers – ImageNet in Keras (VGG16/19, InceptionV3, ResNet50)
• Transfer Learning: Build a Flower & Monkey Breed Classifier
• Design Your Own CNN – LittleVGG: A Simpsons Classifier
• Advanced Activation Functions & Initializations
• Facial Applications – Emotion, Age & Gender Recognition
• Medical Imaging – Image Segmentation with U-Net
• Principles of Object Detection
• TensorFlow Object Detection API
• Object Detection with YOLO & Darkflow: Build a London Underground Sign Detector
• DeepDream & Neural Style Transfers: Make A1 Generated Art
• Generative Adversarial Networks (GANs): Simulate Aging Faces
• Face Recognition with VGGFace
• The Computer Vision World
• BONUS – Build a Credit Card Number Reader
• BONUS – Use Cloud GPUs on PaperSpace
• BONUS – Create a Computer Vision API & Web App Using Flask and AWS

Course content

• Introduction and Outline
• Generative Modeling Review
• Variational Autoencoders
• Generative Adversarial Networks (GANs)
• Theano and Tensorflow Basics Review
• Setting Up Your Environment (FAQ by Student Request)
• Extra Help With Python Coding for Beginners (FAQ by Student Request)
• Effective Learning Strategies for Machine Learning (FAQ by Student Request)
• Appendix / FAQ Finale

About this course

The deep learning models that power AI systems are often black boxes. Explainable AI tries to understand how these models make decisions, so that we can use them responsibly. In this course, you will learn the basic techniques of Explainable AI, including Generative Adversarial Networks (GANs). You will also learn about legal rights to explanation, and the role of explanation in regulating AI.

Skills you’ll gain

• Understand how neural networks function
• Evaluate common Explainable AI methods
• Understand legal rights to explanation