# Torch (10)

**Choosing an Open Source Machine Learning Library: TensorFlow, Theano, Torch, scikit-learn, Caffe**- Nov 8, 2017.

Open Source is the heart of innovation and rapid evolution of technologies, these days. Here we discuss how to choose open source machine learning tools for different use cases.**More Deep Learning “Magic”: Paintings to photos, horses to zebras, and more amazing image-to-image translation**- Apr 17, 2017.

This is an introduction to recent research which presents an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples.**Getting Started with Deep Learning**- Mar 24, 2017.

This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.**An Overview of Python Deep Learning Frameworks**- Feb 27, 2017.

Read this concise overview of leading Python deep learning frameworks, including Theano, Lasagne, Blocks, TensorFlow, Keras, MXNet, and PyTorch.**TensorFlow is Terrific – A Sober Take on Deep Learning Acceleration**- Dec 30, 2015.

TensorFlow does not change the world. But it appears to be the best, most convenient deep learning library out there.**Popular Deep Learning Tools – a review**- Jun 18, 2015.

Deep Learning is the hottest trend now in AI and Machine Learning. We review the popular software for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch.**Deep Learning for Text Understanding from Scratch**- Mar 13, 2015.

Forget about the meaning of words, forget about grammar, forget about syntax, forget even the very concept of a word. Now let the machine learn everything by itself.**Top /r/MachineLearning Posts, Mar 1-7: Stanford Deep Learning for NLP, Machine Learning with Scikit-learn**- Mar 9, 2015.

This week on /r/MachineLearning, we have a new NLP-focused deep learning course from Stanford, an introduction to scikit-learn, visualization of music collections, an implementation of DeepMind, and NLP using deep learning and Torch.**Top /r/MachineLearning posts, Feb 1-7: Music recognition, Text Understanding from scratch**- Feb 9, 2015.

Shazam music recognition techniques, deep learning for text understanding, neuroscience history, Neural Turing Machines using Torch, and genetic algorithms are the top topics on Reddit last week.**Facebook Open Sources deep-learning modules for Torch**- Feb 9, 2015.

We review Facebook recently released Torch module for Deep Learning, which helps researchers train large scale convolutional neural networks for image recognition, natural language processing and other AI applications.