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Episode 61: Sequence Modeling Explained
In this episode of AI Explained, we'll explore "Sequence Modeling" - Sequence modeling enables AI to seemingly anticipate future ...
27:13
MIT 6.S191 (2018): Sequence Modeling with Neural Networks
MIT Introduction to Deep Learning 6.S191: Lecture 2 Sequence Modeling with Neural Networks Lecturer: Harini Suresh January ...
5:55:34
Sequence Models Complete Course
Don't Forget To Subscribe, Like & Share Subscribe, Like & Share If you want me to upload some courses please tell me in the ...
1:14:29
Mamba and S4 Explained: Architecture, Parallel Scan, Kernel Fusion, Recurrent, Convolution, Math
Explanation of the paper Mamba: Linear-Time Sequence Modeling with Selective State Spaces In this video I will be explaining ...
57:34
MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention
MIT Introduction to Deep Learning 6.S191: Lecture 2 Recurrent Neural Networks Lecturer: Ava Amini ** New 2026 Edition ** For ...
4:32
L15.3 Different Types of Sequence Modeling Tasks
Sebastian's books: https://sebastianraschka.com/books/ Slides: ...
1:01:34
MIT 6.S191 (2025): Recurrent Neural Networks, Transformers, and Attention
MIT Introduction to Deep Learning 6.S191: Lecture 2 Recurrent Neural Networks Lecturer: Ava Amini ** New 2025 Edition ** For ...
40:40
Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained)
mamba #s4 #ssm OUTLINE: 0:00 - Introduction 0:45 - Transformers vs RNNs vs S4 6:10 - What are state space models? 12:30 ...
15:57
Mamba: Linear-Time Sequence Modeling with Selective State Spaces (COLM Oral 2024)
Conference on Language Modeling
Authors: Albert Gu, Tri Dao Foundation models, now powering most of the exciting applications in deep learning, are almost ...
56:49
Decision Transformer: Reinforcement Learning via Sequence Modeling (Research Paper Explained)
decisiontransformer #reinforcementlearning #transformer Proper credit assignment over long timespans is a fundamental problem ...
1:29:10
Deep Learning Chapter 10 Sequence Modeling: Recurrent and Recursive Nets presented by Ian Goodfellow
This is a Deep Learning Book Club discussion of Chapter 10: Sequence Modeling: Recurrent and Recursive Nets. Chapter is ...
23:25
Sequence modeling: Hidden Markov Models, part 1
We motivate and discuss the Hidden Markov Model (HMM), including its "states" its "emissions" and the conditional independence ...
5:55:34
Sequence Models (Complete Course)
In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting ...
1:06:35
MedAI #41: Efficiently Modeling Long Sequences with Structured State Spaces | Albert Gu
Title: Efficiently Modeling Long Sequences with Structured State Spaces Speaker: Albert Gu Abstract: A central goal of sequence ...
16:50
Sequence-to-Sequence (seq2seq) Encoder-Decoder Neural Networks, Clearly Explained!!!
In this video, we introduce the basics of how Neural Networks translate one language, like English, to another, like Spanish.
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MAMBA and State Space Models explained | SSM explained
"Mamba: Linear-time sequence modeling with selective state spaces." arXiv preprint arXiv:2312.00752 (2023).
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This is a step-by-step guide to building a seq2seq model in Keras/TensorFlow used for translation. You can follow along and use ...
1:20:43
Stanford CS25: V1 I Decision Transformer: Reinforcement Learning via Sequence Modeling
We introduce a framework that abstracts Reinforcement Learning (RL) as a sequence modeling problem. This allows us to draw ...
17:15
Sequence modeling: Markov assumption
We discuss the Markov assumption, and the related notion of conditional independence. We see how the assumption simplifies ...
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