Kaashiv Infotech
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Microsoft SQL Server 2008 R2 Administration Cookbook
Author: Satya Shyam K. Jayanty
language: en
Publisher: Packt Publishing Ltd
Release Date: 2011-05-24
Over 70 practical recipes for administering a high-performance SQL Server 2008 R2 system with this book and eBook.
VLSI Interview Questions with Answers
If you can spare half an hour, then this ebook guarantees job search success with VLSI interview questions. Now you can ace all your interviews as you will access to the answers to the questions, which are most likely to be asked during VLSI interviews. You can do this completely risk free, as this book comes with 100% money back guarantee. To find out more details including what type of other questions book contains, please click on the BUY link.
Numerical Python
Learn how to leverage the scientific computing and data analysis capabilities of Python, its standard library, and popular open-source numerical Python packages like NumPy, SymPy, SciPy, matplotlib, and more. This book demonstrates how to work with mathematical modeling and solve problems with numerical, symbolic, and visualization techniques. It explores applications in science, engineering, data analytics, and more. Numerical Python, Third Edition, presents many case study examples of applications in fundamental scientific computing disciplines, as well as in data science and statistics. This fully revised edition, updated for each library's latest version, demonstrates Python's power for rapid development and exploratory computing due to its simple and high-level syntax and many powerful libraries and tools for computation and data analysis. After reading this book, readers will be familiar with many computing techniques, including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling, and machine learning. What You'll Learn Work with vectors and matrices using NumPy Review Symbolic computing with SymPy Plot and visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Understand statistical modeling and machine learning with statsmodels and scikit-learn Optimize Python code using Numba and Cython Who This Book Is For Developers who want to understand how to use Python and its ecosystem of libraries for scientific computing and data analysis.