"In this sequel to 'An introduction to machine learning with web data', bit.ly lead scientist Hilary Mason shows you how to solve real-world problems with machine learning. Using real data from an actual ecommerce website, you will apply production quality algorithms to understand all the issues that arise when working in a live environment."--Resource description page.

With Early Release ebooks, you get books in their earliest form-the author's raw and unedited content as he or she writes-so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released. With detailed notes, tables, and examples, this handy reference will help you navigate the basics of...

Get to grips with automated machine learning and adopt a hands-on approach to AutoML implementation and associated methodologies Key Features Get up to speed with AutoML using OSS, Azure, AWS, GCP, or any platform of your choice Eliminate mundane tasks in data engineering and reduce human errors in machine learning models Find out how you can make machine learning accessible for all users to promote decentralized processes Book DescriptionEvery machine...

Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented...

Note: The course is primarily focused on teaching PyTorch and deep learning for computer vision, but it also includes a few sections on the fundamentals of Python (Sections 8-12). These optional learning sections are designed for individuals who may be new to Python or who want to refresh their knowledge of Python basics. In this course, we will take a step-by-step method by first grasping PyTorch's fundamentals. Then, using a guide to getting free...

Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML techniques are clearly explained through graphics and easy-to-grasp examples. In each engaging chapter, you'll put a new algorithm into action to solve a quirky predictive analysis problem, including...

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you'll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists...