Multimodal AI Essentials: Merging Text, Image, and Audio for Next-Generation AI Application
Multimodal AI Essentials: Merging Text, Image, and Audio for Next-Generation AI Application
ISBN: 9780135418536 | .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 5h 32m | 2.02 GB
Instructor: Sinan Ozdemir
ISBN: 9780135418536 | .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 5h 32m | 2.02 GB
Instructor: Sinan Ozdemir
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Introduction
Multimodal AI Essentials: Introduction
Lesson 1: Introduction to Multimodal AI
Topics
1.1 Overview of Multimodal AI Concepts
1.2 Types of Data in Multimodal Systems
1.3 Building a Voice-to-Voice App
Lesson 2: Building Visual Question Answering (VQA) Models
Topics
2.1 Understanding VQA: Concepts and Architecture
2.2 Fusing Modalities to Perform VQA
2.3 Blending Modalities to Perform VQA
Lesson 3: Exploring Diffusion Models
Topics
3.1 Introduction to Diffusion Models
3.2 Hands-On: Implementing Diffusion Models with DreamBooth
Lesson 4: Developing Multimodal AI Systems
Topics
4.1 Designing Multimodal AI Systems
4.2 Fine-Tuning a Text-to-Speech Model with T5
4.3 Building Visual Agents
Lesson 5: Evaluating and Testing Multimodal AI Systems
Topics
5.1 Evaluating Multimodal Models: Accuracy and Performance
5.2 Bias and Ethics in Multimodality
Lesson 6: Expanding and Applying Multimodal AI
Topics
6.1 Extending Multimodal Systems with Advanced Techniques
6.2 Future Trends and Innovations in Multimodal AI
Summary
Multimodal AI Essentials: Summary
Multimodal AI Essentials: Introduction
Lesson 1: Introduction to Multimodal AI
Topics
1.1 Overview of Multimodal AI Concepts
1.2 Types of Data in Multimodal Systems
1.3 Building a Voice-to-Voice App
Lesson 2: Building Visual Question Answering (VQA) Models
Topics
2.1 Understanding VQA: Concepts and Architecture
2.2 Fusing Modalities to Perform VQA
2.3 Blending Modalities to Perform VQA
Lesson 3: Exploring Diffusion Models
Topics
3.1 Introduction to Diffusion Models
3.2 Hands-On: Implementing Diffusion Models with DreamBooth
Lesson 4: Developing Multimodal AI Systems
Topics
4.1 Designing Multimodal AI Systems
4.2 Fine-Tuning a Text-to-Speech Model with T5
4.3 Building Visual Agents
Lesson 5: Evaluating and Testing Multimodal AI Systems
Topics
5.1 Evaluating Multimodal Models: Accuracy and Performance
5.2 Bias and Ethics in Multimodality
Lesson 6: Expanding and Applying Multimodal AI
Topics
6.1 Extending Multimodal Systems with Advanced Techniques
6.2 Future Trends and Innovations in Multimodal AI
Summary
Multimodal AI Essentials: Summary
Multimodal AI Essentials: Merging Text, Image, and Audio for Next-Generation AI Application
