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I am working on implementing hybrid branch predictors listed below
- Gshare + TAGE
- TAGE + Alpha
- Perceptron + TAGE
- Gshare + Alpha
- Perceptron + Gshare
- Perceptron + Alpha
- Perceptron + …
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# Requirements
- [ ] Perceptron model (single layer network).
- [ ] Multi-layer network.
- [ ] At least one application.
### References
> ISBN: 978-1-5386-7808-4
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add to the perceptron note
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# Sunday
Making progress on `homework #1`! 😀
![image](https://user-images.githubusercontent.com/45280066/134831832-c7b44779-511b-49fe-8790-20b041c77c2f.png)
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```python
inputs = [1,2]
weights = [1,1,1]
def perceptron_predict(inputs, weights):
activation = weights[0]
for i in range(len(inputs)-1):
activation += weights[i+1] * inputs…
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https://sunyunqiang.com/blog/perceptron/
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I have tried using the example from `Normalization 101` in the wiki, but I don't know what to do after I have trained the network.
Can I now input 10 new values (e.g. `[1,1,1,0.77,0,1,1,1,0,0]`) and …
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## Coursera - Machine Learning
### Advanced Learning Algorithms
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i have not see the nltk_data in the code ,i do not where is error
[nltk_data] Error loading averaged_perceptron_tagger:
[nltk_data] Error loading cmudict:
![Uploading image.png…]()