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 ...

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, ...

Dr. James McCaffrey of Microsoft Research says the main advantage of scikit is that it's easy to use (even though most classes have many constructor parameters). Logistic regression is a machine ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...

Introduction A few years ago, I was in charge of demand forecasting models at my company. Even though the accuracy was decent ...

Spam filtering, face recognition, recommendation engines — when you have a large data set on which you’d like to perform predictive analysis or pattern recognition, machine learning is the way to go.

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 ...

Data science brings several skills together. Python helps learners work with data programmatically, statistics provides a way to test assumptions and interpret uncertainty, and machine learning adds ...

Overview:  Python’s extensive ecosystem supports everything from data preparation to model training. Go takes a different ...