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AI-For-Beginners
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Fix typos, make improvements

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Dmitri Soshnikov 2021-09-27 11:43:24 +03:00
parent 4c6341b03c
commit 0c554a0905
2 changed files with 2 additions and 2 deletions
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2
3-NeuralNetworks/03-Perceptron/README.md
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@ -60,6 +60,6 @@ def train(positive_examples, negative_examples, num_iterations = 100, eta = 1):
return weights
```
## Proceed in Notebook
## [Proceed to Notebook](Perceptron.ipynb)
To see how we can use perceptron to solve some toy as well as real-life problems, and to continue learning - go to [Perceptron](Perceptron.ipynb) notebook.

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3-NeuralNetworks/README.md
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@ -22,7 +22,7 @@ In this curricula, we will only focus on neural network models.
From biology we know that our brain consists of neural cells, each of them having multiple "inputs" (axons), and an output (dendrite). Axons and dendrites can conduct electrical signals, and connections between axons and dendrites can exhibit different degrees of conductivity (controlled by neuromediators).
![Model of a Neuron](images/synapse-wikipedia.JPG) | ![Model of a Neuron](images/artneuron.png)
![Model of a Neuron](images/synapse-wikipedia.jpg) | ![Model of a Neuron](images/artneuron.png)
----|----
Real Neuron | Artificial Neuron