Beginner Deep Learning Tutorial | MNIST Digits Classification Neural Network in Python, Keras

In this beginner deep learning tutorial we will go through the entire process of creating a deep neural network in Python with Keras to classify handwritten digits. This is a problem which is trivial to a human but much more difficult for a machine, hence why we'll use some machine learning to solve it.

We'll have a high-level overview of the problem, load the data in Python, pre-process the data, build the fully connected network, train and evaluate it on our data, plot a confusion matrix and finally take a look at the mis-classified data to see how they look like and think about why they were not classified correctly by the network.

The only prerequisites for this tutorial are Python programming knowledge, and the will to learn ;) Everything else I'll explain on the way. Please let me know if you have any questions at all.

Contents:
00:00 Introduction
01:19 High Level Overview Presentation
03:19 Creating a Google Colab Notebook
04:14 Imports
05:40 Data Preparation
13:18 Building the Fully Connected Network
15:48 Training
16:53 Evaluation and Inference
21:30 Plotting a Confusion Matrix
24:01 Investigating Errors
29:55 Conclusion

Google Colab:
https://colab.research.google.com

Code:
https://github.com/azinonos/MNIST_DL_Tutorial

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Music Used:
Joakim Karud - Classic

Видео Beginner Deep Learning Tutorial | MNIST Digits Classification Neural Network in Python, Keras канала Andreas Zinonos