From 729ae7ea896340b69a4021e0201b9d1c8d29ee89 Mon Sep 17 00:00:00 2001 From: Martin Pitt Date: Fri, 28 Aug 2020 07:37:04 +0200 Subject: [PATCH] README.md: First steps and resources --- README.md | 35 +++++++++++++++++++++++++++++++ screenshots/numpy-linspace.png | Bin 0 -> 13772 bytes screenshots/numpy-sinpattern.png | Bin 0 -> 109901 bytes 3 files changed, 35 insertions(+) create mode 100644 README.md create mode 100644 screenshots/numpy-linspace.png create mode 100644 screenshots/numpy-sinpattern.png diff --git a/README.md b/README.md new file mode 100644 index 0000000..ad14945 --- /dev/null +++ b/README.md @@ -0,0 +1,35 @@ +# Resources + +Basics: + - [Learn numpy](https://numpy.org/learn/) + - [MNIST database of handwritten digits](http://yann.lecun.com/exdb/mnist/) + - [Neuron](https://en.wikipedia.org/wiki/Artificial_neuron) + - [Perceptron](https://en.wikipedia.org/wiki/Perceptron) + - [3Blue1Brown video series](https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi) + +Too high-level for first-time learning, but apparently very abstract and powerful for real-life: + - [keras](https://keras.io/) + - [tutorial how to recognize handwriting with keras/tensorflow](https://data-flair.training/blogs/python-deep-learning-project-handwritten-digit-recognition/) + +# Dependencies + + sudo dnf install -y python3-numpy python3-matplotlib + +# Steps + + - Do the [NumPy quickstart tutorial](https://numpy.org/devdocs/user/quickstart.html); example: + +```py +import numpy as np +import matplotlib.pyplot as plt +grad = np.linspace(0,1,10000).reshape(100,100) +plt.imshow(grad, cmap='gray') +plt.show() + +plt.imshow(np.sin(np.linspace(0,10000,10000)).reshape(100,100) ** 2, cmap='gray') +# does not work with QT_QPA_PLATFORM=wayland +plt.show(block=False) +plt.close() +``` + + - Get the handwritten digits training data with `./download-mnist.sh` diff --git 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