Course 5 of Andrew Ng's Deep Learning Specialization on Coursera, taught by DeepLearning.AI, covering sequence models such as RNNs, LSTMs, GRUs, word embeddings, attention, and transformers.

Commenters point to it as a clear, mathematically detailed introduction to LSTMs, GRUs, and sequence models, taught by Andrew Ng.

On Reddit (5)

1. Strongly recommendsrskirkpatrick22r/learnmachinelearning2020in “tutorials on RNN for voice recognition/time series/other signals”▲ 2

   Check out Coursera’s “Sequence Models” by deeplearning.ai. It’s taught by Andrew Ng and is a really great course. https://www.coursera.org/learn/nlp-sequence-models

2. Recommendsmr_house7r/LocalLLaMA2023in “How to dive deeper into LLMs?”

   You could try the Sequence Models course in Coursera from deeplearning AI, part of the specialization. You will learn the basics like LSTMs and RNNs, word embedding, Attention mech and Transformers. If you are a little more advanced and know all of the previous mention topics, you could try the…

3. RecommendsHhuziii47r/learnmachinelearning2022in “Intuition for LSTM cell structure”▲ 1

   If you want in-depth understanding then I would recommend you to look for Deep Learning Specialization by Andrew Ng. (Course 4). He explained the LSTM and GRU cells in detail (mathematically). You can also find it on YouTube I guess. Hope it helps.

4. Recommendsnateriver19r/learnmachinelearning2018in “How do I start learning about RNN's? Any good resources?”

   1- Andrej Karpathy blog is a very good ressources 2- Andrew Ng's course on sequence models

5. Mentionsunnamedn00br/learnmachinelearning2018in “Any good resources for learning time series prediction with ML ?”▲ 1

   Search for Ben Lambert on YouTube. He has a long lecture series on statistics/econometrics with a significant portion covering time series. Also check out Rob Hyndman's website where you can go through his free hands-on book on time series forecasting (has R code). For the deep learning variety…

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