• Your ultimate resource for getting up and running with Python numerical computations
• Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules
• A hands-on guide to implementing mathematics with Python, with complete...

• Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0
• Set up your business application to start using machine learning techniques
• Familiarize the user with some of the more common .NET libraries for machine learning
• Implement...

Through a series of recent 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, efficient tools to implement programs capable of learning from data....

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you’ll first start to learn with regression modelling and then move into more...