$ sudo apt-get install -y cmake libgoogle-glog-dev libatlas-base-dev libsuitesparse-dev
$ wget http://ceres-solver.org/ceres-solver-1.14.0.tar.gz
$ tar zxf ceres-solver-1.14.0.tar.gz
$ mkdir ceres-bin
$ mkdir solver &&cd ceres-bin
$ cmake ../ceres-solver-1.14.0 -DEXPORT_BUILD_DIR=ON -DCMAKE_INSTALL_PREFIX="../solver"#good for build without being root privileged and at wanted directory
$ make -j8 # 8 : number of cores
$ make test
$ make install
You can perform Land Cover Classification on Satellite Images using Random Forest and visualize the result using Earthpy package. Make sure to install the required packages and such as
My own NumPy-based implementation of a multilayer perceptron (MLP). Several of its components can be tuned and played with, such as layer depth and size, hidden and output layer activation functions,