Initial commit

.gitignore

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+*.o
+*.a
+*~
+

CMakeLists.txt

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+cmake_minimum_required (VERSION 2.8)
+project (NNet)
+
+SET(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR})
+
+include_directories(src)
+
+set (CMAKE_C_FLAGS "-Wall -std=c99 -O2")
+
+set(LIB_SRC
+   ${PROJECT_SOURCE_DIR}/src/nnet.c
+   ${PROJECT_SOURCE_DIR}/src/loader.c
+   ${PROJECT_SOURCE_DIR}/src/math_utils.c
+)
+
+add_library(nnet STATIC ${LIB_SRC})
+
+set(MAIN_SRC
+   ${PROJECT_SOURCE_DIR}/src/main.c
+)
+
+add_executable(run ${MAIN_SRC})
+target_link_libraries (run "-lgsl -lgslcblas -lm" nnet)
+
+set (CMAKE_CXX_FLAGS "-Wall -std=c++11")
+
+set(TEST_SRC
+   ${PROJECT_SOURCE_DIR}/src/tests.cpp
+)
+
+add_executable(tests ${TEST_SRC})
+target_link_libraries (tests "-lgsl -lgslcblas -lm" nnet)
+

README

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+This is a C implementation of the neural network for handwriting recognition
+outlined in the free online book by Michael Nielsen:
+
+http://neuralnetworksanddeeplearning.com/
+
+It was written as a learning exercise, and is essentially a port of Michael's
+Python implementation here:
+
+https://github.com/mnielsen/neural-networks-and-deep-learning
+
+To use it:
+
+> Install the GNU Scientic library, GCC, G++
+
+> Download the training data:
+
+http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
+http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz
+
+> Unzip the data into ./dat
+
+> Build using cmake eg. from the project directory:
+    > cd build
+    > cmake ..
+    > make
+
+> Run from the project folder:
+    > Tests with ./tests
+    > Train the network with ./run
+
+> Read the book!