Sequence Modeling Courses and Certifications

LearnKartS

Become AI-Ready: Deep Learning Fundamentals

Discover how deep learning powers modern AI systems like ChatGPT through hands-on neural network training, backpropagation, and sequence modeling with RNNs and LSTMs.

• Coursera
• 8 hours 22 minutes
• On-Demand
• Paid Course

Valence Labs

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution

Explore HyenaDNA: a genomic foundation model using long-range context and single nucleotide resolution. Learn about its design, experiments, and state-of-the-art performance in genomic sequence modeling.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Venelin Valkov

Long Sequence Modeling with up to 8K Tokens - Overview, Dataset & Google Colab Code

Explore XGen-7B's capabilities in long sequence modeling, including performance on NLP tasks, code generation, and document comprehension. Hands-on demo using Google Colab.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Alexander Amini;  MIT

MIT: Recurrent Neural Networks

2 reviews

Explore deep sequence modeling with recurrent neural networks, including LSTMs and attention mechanisms. Learn to tackle challenges like vanishing gradients and long-term dependencies in sequence tasks.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Efficiently Modeling Long Sequences with Structured State Spaces - Albert Gu

Explore structured state space models for efficient long sequence modeling across modalities, featuring S4's innovative approach to handling extended dependencies in various data types.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Alexander Amini;  MIT

Recurrent Neural Networks and Transformers

Comprehensive exploration of recurrent neural networks, LSTMs, and attention mechanisms in deep learning, covering theory, implementation, and applications for sequence modeling tasks.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Alexander Amini;  MIT

MIT 6.S191 - Recurrent Neural Networks

Comprehensive lecture on Recurrent Neural Networks, covering theory, implementation, and applications. Explores sequence modeling, LSTM, attention mechanisms, and practical examples in deep learning.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Alexander Amini;  MIT

MIT 6.S191 - Recurrent Neural Networks

Explore recurrent neural networks, LSTMs, and attention mechanisms for sequence modeling. Learn backpropagation through time, gradient issues, and practical applications in deep learning.

• YouTube
• 45 minutes
• On-Demand
• Free Video

Yannic Kilcher

Can Wikipedia Help Offline Reinforcement Learning? - Paper Explained

Exploring how pre-training on Wikipedia improves offline reinforcement learning models, enhancing performance, reducing parameters, and revealing connections between language and RL domains.

• YouTube
• 39 minutes
• On-Demand
• Free Video

Yannic Kilcher

Infinite Memory Transformer - Research Paper Explained

Explores innovative Transformer model with unbounded memory, enabling processing of arbitrarily long sequences. Discusses continuous attention mechanisms, sticky memories, and potential applications in language modeling.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Alexander Amini

Recurrent Neural Networks, Transformers, and Attention - MIT 6.S191 Lecture 2

Dive into recurrent neural networks, transformers, and attention mechanisms with MIT's Introduction to Deep Learning lecture by Ava Amini.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Discover AI

Mamba AI: Understanding Selective State Space Models as Transformer Alternatives

Explore the groundbreaking MAMBA architecture and its potential to revolutionize AI through selective state space models, offering a compelling alternative to traditional transformers.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Valerio Velardo - The Sound of AI

Melody Generation with RNN-LSTM

Master melody generation using Long Short-Term Memory networks to create AI-composed music from preprocessing datasets to converting neural network outputs into MIDI files.

• YouTube
• 4 hours 56 minutes
• On-Demand
• Free Video

Graham Neubig

CMU Advanced Natural Language Processing Spring 2024

Master advanced NLP techniques from transformers to LLMs, covering prompting, fine-tuning, RAG, reinforcement learning, code generation, and multilingual processing in this comprehensive series.

• YouTube
• 1 day 1 hour 26 minutes
• On-Demand
• Free Video

Graham Neubig

CMU Advanced Natural Language Processing 2022

Master advanced NLP techniques from text classification to transformers, covering attention mechanisms, pre-training methods, prompting, bias detection, and structured learning algorithms.

• YouTube
• 1 day 6 hours 23 minutes
• On-Demand
• Free Video