FreeGym.ai
AbhinavDemocratize Fitness
| Platform |  | Pricing | Only free issues | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 42 | Founded | 3 years ago | Last Issue | 3 years ago |
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13.7. Attention and Transformer Models (RNN)
Problem with Long Sequences in RNNs
- Sequence Length and Computation: The longer the sequence, the harder it becomes for RNNs, including LSTMs and GRUs, to process it efficiently and retain information from the initial parts of the...
13.6. Embeddings and Word Representations (RNN)
Introduction to Embeddings
- What is an Embedding?: An embedding, in the context of machine learning and specifically natural language processing (NLP), refers to the conversion of discrete categorical variables (like words) into con...
13.5. Backpropagation Through Time (BPTT) and RNN Training
Understanding BPTT: Unfolding Computation Graphs
- RNNs as Unfolded Computational Graphs: When training RNNs, it's helpful to visualize them as an "unfolded" version across time steps. This reveals the sequential nature of RNNs, wher...
13.4. Advanced RNNs (GRU and LSTM)
Introduction to Gated Recurrent Units (GRUs)
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GRUs were introduced as an alternative to vanilla RNNs to address the vanishing gradient problem and better capture long-term dependencies.
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They use gating mechanisms to regulate th...
13.3. Working and Mathematics of Vanilla RNNs
Working and Mathematics of Vanilla RNNs
A vanilla RNN, also known as a simple or Elman RNN, processes inputs sequentially, maintaining an internal state (hidden state) that encodes information about the inputs it has processed so far....
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The writers behind this newsletter.
Fitness Innovator | Co-Founder, FreeGym | On the last day of my life, when none of this will matter, I want to be proud of myself.
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