1 # Resources
3 Basics:
4  - [Learn numpy](https://numpy.org/learn/)
5  - [MNIST database of handwritten digits](http://yann.lecun.com/exdb/mnist/)
6  - [Neuron](https://en.wikipedia.org/wiki/Artificial_neuron)
7  - [Perceptron](https://en.wikipedia.org/wiki/Perceptron)
8  - [Backpropagation](https://en.wikipedia.org/wiki/Backpropagation)
11 Too high-level for first-time learning, but apparently very abstract and powerful for real-life:
12  - [keras](https://keras.io/)
13  - [tutorial how to recognize handwriting with keras/tensorflow](https://data-flair.training/blogs/python-deep-learning-project-handwritten-digit-recognition/)
15 # Dependencies
17     sudo dnf install -y python3-numpy python3-matplotlib
19 # Steps
21  - Do the [NumPy quickstart tutorial](https://numpy.org/devdocs/user/quickstart.html); example:
23 ```py
24 import numpy as np
25 import matplotlib.pyplot as plt
28 plt.show()
30 plt.imshow(np.sin(np.linspace(0,10000,10000)).reshape(100,100) ** 2, cmap='gray')
31 # non-blocking does not work with QT_QPA_PLATFORM=wayland
32 plt.show(block=False)
33 plt.close()
34 ```