As promised, we have come up with yet another list of some lesser known Machine Learning Libraries that you might find interesting.
This is one of those Machine Learning Libraries that are primarily used to the serve the purpose of optimization.
This is an intuitive library to add plotting functionality to scikit-learn objects.
Opt can generate different variations of the solver that helps the users to easily explore tradeoffs in numerical precision, matrix-free methods, and solver approaches.
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
Baidu has taken an algorithm named the “ring allreduce,” from the high-performance computing (HPC) world and brought it to deep learning to increase the efficiency of its GPU nodes.
This is a tool for reading and writing datasets of tensors in a Lightning Memory-Mapped Database (LMDB). This library is designed to manage machine learning datasets with fast reading speeds.
It is a 3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL.
liquidSVM is a package written in C++ that provides SVM-type solvers for various classification and regression tasks. It provides unprecedented speed for small training sizes as well as for data sets of tens of millions of samples.
LIBIRWLS is an integrated library that makes use of a parallel implementation of the Iterative Re-Weighted Least Squares (IRWLS) procedure for solving the quadratic programmig (QP) problem that arises during the training of Support Vector Machines (SVMs).
scikit-feature is an open-source feature selection repository in Python built upon one widely used machine learning package scikit-learn and two scientific computing packages Numpy and Scipy.
ArrayFire is a high performance library for parallel computing with an easy-to-use API. It enables users to write scientific computing code that is portable across CUDA, OpenCL and CPU devices.
MShadow is a lightweight CPU/GPU Matrix/Tensor Template Library in C++/CUDA.
Libmvec is vector math library added in Glibc 2.22 to support SIMD constructs of OpenMP4.0
This is Cython implementation of k-MC2 and AFK-MC2 seeding for K nearest neighbhour clustering algorithm.
Pymanopt is a Python toolbox for optimization on manifolds, that computes gradients and Hessians automatically.
CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.
TPOT is a Python tool that is built on top of scikit-learn, that automatically creates and optimizes machine learning pipelines using genetic programming.
If you know what type of classifier you wish to use on your dataset, you can let hpsklearn know and it will only search in the parameter space of the given classifier.
sklearn-crfsuite is a python-crfsuite wrapper which provides you the scikit-learn-compatible sklearn_crfsuite.CRF estimator. This is an amzing yet not very popular among the machine learning libraries.
That’s a wrap to our list of some lesser-known Machine Learning Libraries. If you have something to contribute to the list, comment below and share your thoughts.