ct. 18, 1995 v. 1.00 =========================================================================== + First release of CurveExpert 1.0. Oct. 26, 1995, v. 1.01 =========================================================================== New Features: + M
Writing Testbenches using System Verilog 英文原版的，学起来比较容易。 Writing Testbenches using System Verilog About the Cover xiii Preface xv Why This Book Is Important . . . . . . xvi What This Book Is About . . . . . . . . xvi What Prior Knowledge You Should H
笔记本的风扇控制 ---------------------------------------- 09 November 2006. Summary of changes for version 20061109: 1) ACPI CA Core Subsystem: Optimized the Load ASL operator in the case where the source operand is an operation region. Simply map the opera
The first thing we do is choose a device and check to see whether it supports a feature known as device overlap. A GPU supporting device overlap possesses the capacity to simultaneously execute a CUDA C kernel while performing a copy between device
Since the introduction of support vector machines, we have witnessed the huge development in theory, models, and applications of what is so-called kernel-based methods: advancement in generalization theory, kernel classifiers and regressors and thei
Today, it’s widely accepted that developers should write automated tests that fail the build if they find regressions. Furthermore, an increasing number of professionals is leaning on a test-first style of programming, using automated tests not for
We propose a new regression method to evaluate the impact of changes in the distri- bution of the explanatory variables on quantiles of the unconditional (marginal) distrib- ution of an outcome variable. The proposed method consists of running a reg
Master high quality software development driven by unit tests About This Book Design and implement robust system components by means of the de facto unit testing standard in Java Reduce defect rate and maintenance effort, plus simultaneously increas
NET is one of the widely used platforms for developing applications. With the meteoric rise of machine learning, developers are now keen on finding out how to make their .NET applications smarter using machine learning. Mastering .NET Machine Learni
Data Science Essentials in Python: Collect – Organize – Explore – Predict – Value https://pragprog.com/book/dzpyds/data-science-essentials-in-python Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized da
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of conc
What You’ll Learn Extend your machine learning models using simple techniques to create compelling and interactive web dashboards Leverage the Flask web framework for rapid prototyping of your Python models and ideas Create dynamic content powered b
This release contains a number of fixes for regressions introduced in 0.22.0, where we shipped a significant refactoring to the way geckodriver internally dealt with JSON serialisation. Removed The POST /session/{session id}/element/{element id}/tap
This paper tests the relationship between average return and risk for New York Stock Exchange common stocks. The theoretical basis of the tests is the "two-parameter" portfolio model and models of market equilibrium derived from the two-parameter po
