Backup and Restore Improvements

The lines between on-premise and public cloud services have become blurred. The integration between on-premise and off-premise technologies imply that you can now easily implement a backup solution that makes use of both, thus allowing you to maintain up-to-date backups both on-site and off-site. This will allow you to implement a disaster recovery plan that meets strict service-level agreements without having to invest in a Disaster Recovery (DR) site. The DR site can be in the cloud. Depending on your environment, this can significantly reduce the cost of implementing a fully blown disaster recovery site or server room.

There are several new features in SQL Server 2014 that make this possible; they are as follows:

• Backup to URL

• Backup to Microsoft Azure

• Encryption

In this article by Gethyn Ellis, the author of Getting Started with SQL Server 2014 Administration, you will look at how you can make use of the new features and integrate them into your backup and recovery plans to ensure that you maintain up-to-date off-site backups.

Using cross-validation

In this article by Akhil Wali, author of Clojure for Machine Learning, we will discuss several methods that can be used to improve the effectiveness of a given machine learning model. We will also implement a working spam classifier as an example of how to build machine learning systems that incorporate evaluation.

The Fastest Way to Go from an Idea to a Prezi

In this article, by Hedwyg van Groenendaal, the author of Prezi Hotshot, we will be using the brainstorming techniques in Prezi. It is easy to create a good prezi. We will go from brainstorming to a mind map and use that as a basis for our prezi.

Best Practices for Modern Web Applications

In this article by Daniel Li, author of Mastering Grunt, we will cover the best practices for frontend development today. It will cover load time reduction, search engine optimization, form validation, and responsive design.

Skinning a character

In this article, by Sumeet Arora, the author of WebGL Game Development, we discuss various aspects of skinning a character.

Monte Carlo Simulation and Options

In this article by Yuxing Yan, the author of Python for Finance, discusses how to use Monte Carlo simulation to price European, American, average, lookback, and barrier options.

In finance, we study the trade-off between risk and return. The common definition of risk is uncertainty. For example, when evaluating a potential profitable project, we have to predict many factors in the life of the project, such as the annual sales, price of the final product, prices of raw materials, salary increase of employees, inflation rate, cost of borrowing, cost of new equity, and economic status. For those cases, the Monte Carlo simulation could be used to simulate many possible future outcomes, events, and their various combinations. In this article, we focus on the applications of the Monte Carlo simulation to price various options.