These are the solutions to all exercises accompanying my lecture DeepLearning
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01_convolution_demo
02_mnist
03_perceptron_learning_rule
04_multi_layer_perceptron
05_backpropagation
07_tensorflow_basics
08_tensorflow_a_first_cnn
09_tensorflow_alexnet
11_hebbian_learning_solution
11_hebbian_learning_start
12_lstm
MNIST
lecture_examples/autoencoder
README.md
solutions_exercises_deep_learning.sln

README.md

Solutions-Exercises-DeepLearning

These are the solutions to all exercises accompanying my lecture DeepLearning.

Some of the solutions are written in C++ using OpenCV.

Some others are written in Python using TensorFlow or TensorFlow+Keras.

For the C++ projects:

I will only setup the Debug/X86 (32 bit) project configuration. So when switching to Release/X86 you will have to set up the include-paths, library paths, list of .lib files to link against and the runtime library by your own.

Make sure you define the OPENCV_DIR environment variable (before starting Visual Studio!) to the path where you store your OpenCV version.