Scikit Learn Scikit-learn is a machine learning library for Python. It features several regression, classification and clustering algorithms including SVMs, gradient boosting, k-means, random forests and DBSCAN. It is designed to work with Python Numpy and SciPy. The scikit-learn project kicked off as a Google Summer of Code (also known as GSoC) project by David […]
Keras Deep Learning Tutorial
What is Keras? Keras is a high-level neural networks API. It is written in Python and can run on top of Theano, TensorFlow or CNTK. It was developed with the idea of: Being able to go from idea to result with the least possible delay is key to doing good research. Keras is a user-friendly, […]
Python TensorFlow Tutorial
TensorFlow was developed for Google’s internal use by Google Brain team, but the system is general enough to be applied to a wide variety of domains. On November 9, 2015, they decided to open source it, and release it under Apache 2.0 open source license. Today we will look into TensorFlow basics and then some […]
Theano Python Tutorial
Theano is a numerical computation library for Python. It is a common choice for implementing neural network models as it allows you to efficiently define, optimize and evaluate mathematical expressions, including multi-dimensional arrays (numpy.ndaray). Theano Python Theano makes it possible to attain high speeds that give a tough competition to hand-crafted C implementations for problems […]