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# vanishing and exploding gradient / sensitivity
- (**must see**) X. Glorot and Y. Bengio. Understanding the difficulty of trainingdeep feedforward neural networks. InAISTATS, 2010.
- (**must see**)…
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Currently the model always takes greedy decision for each step in the sequence path. During prediction, this is usually not optimal as the best path may not be the greedy path. Beam search is often us…
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I'm wondering if could you specify what kind of architectures you used in this project? Based on recurrent networks, CRFs, etc.? :)
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- [X] I have searched the existing issues
## Feature Description
### HeartBeat Classification using ECG
This project focuses on developing a system for classifying heartbeats using Electr…
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# Question : Implement a program for real-time recommendation systems based on quantum deep reinforcement learning with recurrent neural networks.
Path to create the file : `004ENw/DRqQ0F.cs`
To as…
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Good understanding of deep learning architectures like Multi-Layer Perceptron, Recurrent Neural Networks (RNNs), Long Short Term Memory models (LSTMs), Gated Recurrent Units (GRUs), and Convolutional …
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### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : Flight Fare Prediction
:red_circle: **Aim** : Building Flask web app which predicts fare of Flight tick…
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Research a few possible models we can use to generate text. Possibilities:
* Markov chains: should be relatively easy to implement on our own but likely wouldn't give great results.
* Recurrent ne…
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**Description:**
Predicting future traffic flow, which will aid in traffic management and planning. The goal is to build a model that can accurately forecast traffic flow based on historical data a…
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### Evaluation
- [ ] [Confusion matrices](https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62)
- [Source 2](https://en.wikipedia.org/wiki/Confusion_matrix)
- [ ] [Precision…