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Introduction to Transformers in NLP
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Classroom Contents
All-in-One Artificial Intelligence Full Course 2024 - AI Tutorial for Beginners
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- 1 Introduction
- 2 Introduction to Artificial Intelligence
- 3 History of AI
- 4 AI vs Machine Learning vs Deep Learning
- 5 Introduction to Neural Networks
- 6 Introduction To Deep Learning
- 7 What is Back Propagation
- 8 How does Back propagation works
- 9 What is Back and Forward Propagation
- 10 What is Feed Forward Network
- 11 Types of Back Propagation Network
- 12 Key Points of Back Propagation
- 13 Demo for Back Propagation Function Implementation
- 14 Human brain vs Neural Network
- 15 Introduction for TensorFlow
- 16 Getting Started with TensorFlow
- 17 How to Install TensorFlow
- 18 Demo 1 MNIST Character Recognition with TensorFlow
- 19 Introduction to Computer Vision
- 20 Filters
- 21 Features from Kernels
- 22 Case Study on Image Processing
- 23 Convolution Layer
- 24 Pooling and Padding
- 25 CNN Architecture
- 26 Transfer Learning
- 27 Case Study on Image Classifier
- 28 Introduction to OpenCV
- 29 Process of OpenCV
- 30 How to Install OpenCV
- 31 Demo on OpenCV Operations
- 32 Introduction to NLP
- 33 Tokenization
- 34 Sequence to Sequence Model
- 35 Introduction to Transformers in NLP
- 36 Introduction to Generative AI
- 37 What is Prompt Engineering
- 38 AI Projects and Case Studies
- 39 Summary
