Encoder-Decoder Models Courses and Certifications

Natural Language Processing on Google Cloud

540 ratings at Coursera

Explore NLP on Google Cloud: from APIs to advanced models. Learn AutoML, custom training, and end-to-end workflows using Vertex AI and TensorFlow. Covers text representation, neural networks, and state-of-the-art techniques.

• Coursera
• 8 hours 55 minutes
• Self-Paced
• Paid Course

Create Image Captioning Models

32 ratings at Coursera

Learn to build deep learning models that generate captions for images, covering encoder-decoder architecture, training techniques, and evaluation methods for practical implementation.

• Coursera
• 52 minutes
• Self-Paced
• Paid Course

Edureka

Neural Models and Machine Translation

Discover neural architectures like RNNs, LSTMs, and Transformers to build powerful machine translation systems and NLP applications with hands-on fine-tuning exercises.

• Coursera
• 17 hours 8 minutes
• Self-Paced
• Paid Course

Neuro Symbolic

LLM Tutorial - Introduction to Language Models, Prompt Engineering, and Encoder-Decoder Architectures

Discover LLM fundamentals, prompt engineering techniques, and explore both encoder and decoder architectures while understanding model limitations and hallucinations.

• YouTube
• 1 hour 43 minutes
• Self-Paced
• Free Video

Create Image Captioning Models

1 rating

Learn to build deep learning models that generate captions for images, covering encoder-decoder architecture, training, and evaluation techniques.

• Google Skills
• 30 minutes
• Self-Paced
• Free Certificate

Shaping the Future of AI from the History of Transformer Architectures - Stanford CS25

Explore the evolution of Transformer architectures and AI development with OpenAI researcher Hyung Won Chung, focusing on historical motivations and future projections in the field.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Lennart Svensson

Introduction to Transformer Architecture - Complete Video Series

1 rating

Dive into transformer architecture fundamentals through self-attention, encoders, decoders, and applications in NLP tasks like translation and text generation.

• YouTube
• 1 hour 40 minutes
• Self-Paced
• Free Video

Alexander Amini;  MIT

MIT 6.S191 - Automatic Speech Recognition

Explore automatic speech recognition with Rev.com experts, covering data selection, speech input processing, and advanced ASR techniques like attention-based models and language modeling.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

Abhishek Thakur

Introduction to T5 for Sentiment Span Extraction

Explore T5's text-to-text approach for NLP tasks, focusing on sentiment span extraction in tweets. Learn about multi-task learning and its potential impact on industrial NLP applications.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Graham Neubig

CMU Advanced NLP 2021 - Conditional Generation

Learn advanced NLP techniques for conditional generation, including encoder-decoder models, search algorithms, ensembling, and evaluation methods. Explore applications in translation, summarization, and dialogue systems.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

Graham Neubig

Neural Nets for NLP 2021 - Conditioned Generation

Explore encoder-decoder models, conditional generation, search techniques, ensembling, evaluation methods, and various data types for conditioning in neural network-based natural language processing.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Graham Neubig

Neural Nets for NLP 2019 - Attention

Explore attention mechanisms in neural networks for NLP, covering basic concepts, improvements, specialized varieties, and a case study on the Transformer model.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

Graham Neubig

Neural Nets for NLP 2017 - Conditioned Generation

Explore encoder-decoder models, conditional generation, ensembling, and evaluation techniques for neural networks in natural language processing. Gain insights into advanced NLP concepts and practical applications.

• YouTube
• 1 hour 2 minutes
• Self-Paced
• Free Video

Andreas Geiger

Attacking Optical Flow

Explores adversarial patch attacks on optical flow networks, revealing vulnerabilities in deep learning-based motion estimation crucial for autonomous driving safety.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

CodeEmporium

Transformers - From Zero to Hero

Comprehensive deep dive into transformer architecture, covering key concepts from self-attention to tokenization. Includes hands-on coding for both encoder and decoder implementations.

• YouTube
• 3 hours 35 minutes
• Self-Paced
• Free Video