Teaching yourself deep learning is a long and arduous process. You need a strong background in linear algebra and calculus, good Python programming skills, and a solid grasp of data science, machine ...

Over the past year I’ve reviewed half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and ...

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models. If you’re starting a new machine learning or deep learning ...

PyTorch 1.0 shines for rapid prototyping with dynamic neural networks, auto-differentiation, deep Python integration, and strong support for GPUs Deep learning is an important part of the business of ...

Gadget Book: Introduction to Computer Organization: ARM Edition It covers the ARM 64-bit assembly language programming, and ...

Overview Beginner-friendly books simplify Python, R, statistics, and machine learning concepts.Practical examples and ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Social scientists are increasingly adopting machine learning methods to analyze ...

While Microsoft has been doggedly chasing Amazon Web Services (AWS) in the cloud computing arena, the two tech giants have partnered on a new deep learning initiative called Gluon. It's desribed as an ...