5 Books That Work in Practical Python Machine Learning

Introduction A few years ago, I was tasked with creating a demand forecasting prototype on the side of my regular work. I ...
InfoWorld

Review: Scikit-learn shines for simpler machine learning

Scikits are Python-based scientific toolboxes built around SciPy, the Python library for scientific computing. Scikit-learn is an open source project focused on machine learning: classification, ...
InfoWorld

The best machine learning and deep learning libraries

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 ...
Computerworld

Review: The best frameworks for machine learning and deep learning

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 ...
Visual Studio Magazine

Binary Classification Using a scikit Neural Network

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...

5 Practical Books for Python Machine Learning

Introduction I first started working with machine learning in earnest when I took on a small project to classify internal inquiry logs. I managed to get scikit-learn code running by piecing together ...