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 ...

Master important frameworks for deep learning in Python Data Science with "Tensorflow and Keras Masterclass For Machine Learning and AI in Python".

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.

With the addition of the high-level Gluon API, Apache MXNet rivals TensorFlow and PyTorch for developing deep learning models When I reviewed MXNet v0.7 in 2016, I felt that it was a promising ...

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 ...

Parting thoughts Deep learning is an exciting and fast-changing field with new methods emerging regularly. It might seem like a daunting task for social scientists to adopt these new tools. However, ...

Python, as a simple yet powerful programming language, has gained increasing popularity in recent years. With the expansion ...