Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, ...

Learn to use open source software like Python, Pandas, Numpy, Scikit-learn and Bokeh to build predictive models from a real-world data. The course is lead by Francesco Mosconi. Ph.D. in Physics 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 ...

I was pleased to receive a review copy of this new title from Cambridge University Press, “A Hands-on Introduction to Machine Learning.” The hardcover book is very attractive, well-produced and solid!

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

Machine learning is a fascinating and rapidly growing field revolutionizing various industries. If you’re interested in diving into the world of machine learning and developing your skills, YouTube ...

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 ...

A comprehensive Python library for machine learning and predictive data analysis. With limited support for deep learning, Scikit-learn offers a large number of algorithms and easy integration with ...