Machine Learning: Modern Computer Vision & Generative Ai

Machine Learning: Modern Computer Vision & Generative Ai
Published 10/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz

Use KerasCV, Python, Tensorflow, PyTorch, & JAX for Image Recognition, Object Detection, and Stable Diffusion

What you’ll learn

Computer vision with KerasCV

How to do image classification / image recognition with a pretrained model and fine-tuning / transfer learning

How to do object detection with a pretrained model and fine-tuning / transfer learning

How to generate images with Stable Diffusion in KerasCV

Requirements

Experience with Keras

Description

Overview

Section 1: Introduction

Lecture 1 Introduction & Outline

Lecture 2 How to Succeed in This Course

Lecture 3 Where to Get the Code

Section 2: Image Classification, Fine-Tuning and Transfer Learning

Lecture 4 Classification Section Outline

Lecture 5 Concepts: Pre-trained Image Classifier

Lecture 6 Pre-trained Image Classifier in Python

Lecture 7 Transfer Learning and Fine-Tuning

Lecture 8 Fine-Tuning an Image Classifier in Python

Lecture 9 Classification Exercise

Lecture 10 Suggestion Box

Section 3: Object Detection

Lecture 11 Object Detection Outline

Lecture 12 Concepts: Object Detection

Lecture 13 Decoding the Output: IoU, Non-Max Suppression, Confidence Score

Lecture 14 Pre-trained Object Detection in Python

Lecture 15 Focal Loss & Smooth L1 Loss

Lecture 16 Object Detection Dataset Formats (COCO & Pascal VOC)

Lecture 17 LabelImg Setup

Lecture 18 LabelImg Demo

Lecture 19 Data Augmentation

Lecture 20 KerasCV Object Detection Dataset Format

Lecture 21 Fine-Tuning Object Detection in Python (Built-In Dataset)

Lecture 22 Fine-Tuning Object Detection in Python (Custom Dataset)

Lecture 23 Object Detection Exercise

Section 4: Generative AI with Stable Diffusion

Lecture 24 Stable Diffusion Outline

Lecture 25 Generate Images with Stable Diffusion in Python

Lecture 26 How Do Diffusion Models Work? (Optional)

Lecture 27 Diffusion Model Architecture (Optional)

Lecture 28 How Diffusion Models Condition on Prompts (Optional)

Lecture 29 A Look at the Diffusion Model Source Code (Optional)

Beginner to advanced students and professionals interested in computer vision with KerasCV