Sequence to Sequence Models Courses and Certifications

Toronto Machine Learning Series (TMLS)

Pre-Trained Multilingual Sequence to Sequence Models for NMT - Tips, Tricks and Challenges

Explore pre-trained multilingual sequence-to-sequence models for Neural Machine Translation. Learn adaptation techniques, training tips, and evaluation strategies while addressing challenges in implementation.

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

UofU Data Science

Introduction to Machine Translation with Sequence-to-Sequence Models

Master sequence-to-sequence modeling fundamentals and applications in machine translation, focusing on neural network architectures and practical implementation techniques.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Sequence Models

31244 ratings at Coursera

Master sequence models for NLP tasks, including RNNs, LSTMs, and transformers. Apply these techniques to speech recognition, language modeling, and machine translation.

• Coursera
• 1 day 13 hours 7 minutes
• Self-Paced
• Paid Course

Graham Neubig

Multilingual Natural Language Processing 2020

Explore multilingual NLP techniques from typology to machine translation, covering cross-lingual transfer, speech processing, and low-resource language challenges.

• YouTube
• 17 hours 52 minutes
• Self-Paced
• Free Video

Sequence Models & The Dawn of Attention

Discover why RNNs and LSTMs fail with long sequences, then master attention mechanisms by building QKV paradigms and reusable PyTorch modules from scratch.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Center for Language & Speech Processing(CLSP), JHU

Machine Translation 1

Dive into foundational machine translation concepts and techniques through comprehensive coverage of statistical and neural approaches to automated language translation.

• YouTube
• 2 hours 55 minutes
• Self-Paced
• Free Video

UofU Data Science

Introduction to Neural Machine Translation and Language Processing

Master the fundamentals of neural machine translation, from embedding matrices and RNNs to advanced concepts like teacher forcing, decoding methods, and BLEU score evaluation metrics.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Natural Language Processing with Sequence Models

1181 ratings at Coursera

Train neural networks for sentiment analysis, text generation, named entity recognition, and question comparison using advanced NLP techniques like GLoVe embeddings, GRUs, LSTMs, and Siamese models.

• Coursera
• 21 hours 6 minutes
• Self-Paced
• Paid Course

Graham Neubig

CMU Multilingual NLP - Machine Translation-Sequence-to-Sequence Models

Explore conditional language modeling, sequence-to-sequence models, generation methods, attention mechanisms, and transformers in multilingual natural language processing.

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

Simons Institute

Towards Sequence-to-Sequence Models Without Activation Functions

Explore how high-order interactions can replace activation functions in neural networks, examining their effectiveness in image recognition, arithmetic tasks, and language modeling.

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

UofU Data Science

Sequence-to-Sequence Models Through the Lens of Neural Machine Translation

Explore sequence-to-sequence models and neural machine translation fundamentals in this comprehensive data science presentation from University of Utah.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Creating Sequence Models and Transformers

Master sequence modeling and transformers—from RNNs, LSTMs, and Seq2Seq to self-attention and fine-tuning—using PyTorch and HuggingFace to build a transformer-based Q&A system.

• Udacity
• 11 hours
• Self-Paced
• Paid Course

Stanford CS224N - Natural Language Processing with Deep Learning 2023

Master cutting-edge neural networks for NLP, from word vectors to Transformers, with hands-on tutorials covering RNNs, attention mechanisms, and modern language models.

• YouTube
• 1 day 5 hours 12 minutes
• Self-Paced
• Free Video

Stanford CS224N - Natural Language Processing with Deep Learning - Winter 2021

Master neural networks, transformers, and attention mechanisms for text processing, translation, and language generation through Stanford's comprehensive deep learning approach.

• YouTube
• 1 day 7 hours 31 minutes
• Self-Paced
• Free Video

Deep Learning: Advanced Natural Language Processing and RNNs

7464 ratings at Udemy

Natural Language Processing (NLP) with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!

• Udemy
• 8 hours 22 minutes
• Self-Paced
• Paid Course