by Karan Asher A quick guide to deploying your Python webapp on Google App Engine Image credit. https://www.python.org/, [https://www.python.org/] https://medium.com/@javidgon/google-cloud-storage-pros-cons-and-how-to-use-it-with-javascript-ea9ce60a94c0 The growth in the number of web-based applications and frameworks in the recent times is astounding. As companies such as Google, Amazon, and Microsoft provide more and more easy-to-use tools to build and deploy applications, it makes more sens
As a Data Scientist, I code almost entirely in Python. Using the pipenv/pyenv combo for Python makes my life slightly less terrifying.
Introduction to linear regression: Linear regression is the first prediction algorithm taught in statistics to the students who begin their journey …
The past few months, I encountered one term again and again in the data science world: Markov Chain Monte Carlo. In my research lab, in podcasts, in articles, every time I heard the phrase I would…
Blue box has met Big blue.
Introduction to linear regression: Linear regression is the first prediction algorithm taught in statistics to the students who begin their journey …
Introduction to linear regression: Linear regression is the first prediction algorithm taught in statistics to the students who begin their journey …
List comprehension is a compact way of creating lists. It’s a more Pythonic and efficient way to create lists than traditional methods. For example, [x**2 for x in range(10)] creates a list of…
Nowadays, companies recognized the benefits of centralized management and control and moved to a model where data is stored on, and many apps are run from, servers on the local network. The next step will move apps and data storage even farther away from the end user, into the "cloud," with everything residing on remote servers accessed via the Internet. And Cloud Computing requires that a computing platform exist "out there" in the cloud, on which these remote apps can run. A number of cloud platforms are available from different vendors, including Amazon, IBM, and Google, among others. Azure is Microsoft's cloud-based application platform for developing, managing, and hosting applications off-site. Azure consists of several components such as the cloud operating system itself; SQL Azure, which provides database services in the cloud; and .NET services. Azure runs on computers that are physically located in Microsoft data centers. Azure was announced in October 2008. At the initial stage, it started with codename "Project Red Dog" and released on February 1, 2010. It called "Windows Azure" before being renamed "Microsoft Azure" on March 25, 2014. Microsoft Azure uses a specialized operating system, called Microsoft Azure, to run its "fabric layer" - a cluster hosted at Microsoft's data centers that manage computing and storage resources of the computers and provisions the resources (or a subset of them) to applications running on top of Microsoft Azure. Microsoft Azure has been described as a "cloud layer" on top of a number of Windows Server systems, which use Windows Server 2008 and a customized version of Hyper-V, known as the Microsoft Azure Hypervisor to provide virtualization of services. Azure provides software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS) and supports many different programming languages, tools, and frameworks, including both Microsoft-specific and third-party software and systems. It provides a range of cloud services, including those for compute, analytics, storage, and networking. Users can pick and choose from these services to develop and scale new applications, or run existing applications, in the public cloud. Azure offers two deployment models for cloud resources: the "classic" deployment model and the Azure Resource Manager. In the classic model, each Azure resource (virtual machine, SQL database, etc.) was managed individually. The Azure Resource Manager, introduced in 2014, enables users to create groups of related services so that closely coupled resources can be deployed, managed, and monitored together. Reasons to use Azure Azure is based on Windows, so you can write applications in the same programming languages you've used for Windows apps: Visual Basic, C++, C#, etc. You can also use familiar tools such as Visual Studio, along with ASP.NET and other familiar Windows technologies. This makes it easy for organizations to find developers who already have the skills to create applications for the Azure platform. Azure supports open standards and Internet protocols, such as HTTP, XML, SOAP, and REST. There are SDKs for Java, PHP, and Ruby, for applications written in those languages, and Azure tools for Eclipse. Azure can benefit hosting providers, ISVs, systems integrators, and custom software, developers. ISVs can use Azure to create, deploy, and manage Web apps and SaaS without large capital expenditures, and they can scale those applications more quickly and cost-effectively. With Azure, it's easier to create a cloud version of an existing Windows application. Applications running on Azure run in virtual machines, with each instance of the app running in its own VM on the 64-bit Windows Server operating system. With Azure, you can focus on the code and don't have to worry about the hardware. Microsoft provides Azure software development kit (SDK), which includes a version of the Azure environment you can run on your own computer. Using Azure, you can easily create applications that run reliably and scale from 10 to 10 thousand or even 10 million users without any additional coding. Azure Storage provides scalable, secure, performance-efficient storage services in the cloud. A Web app can specify the number of processors for the application to use. If the application needs to scale up to meet growing demand, it's easy to change the settings to use more processors. Taking advantage of resources in the cloud allows you to decrease your costs for building and expanding your on-premises resources. You can also reduce the cost of IT administration because the hardware is being taken care of for you, off-premises. The cost of creating, testing, debugging, and distributing Web-based applications goes down because you have to pay only for the computer processing time and storage space you need at a given time. SQL Azure provides organizations with all the benefits of an enterprise-class data center without the hassle, headaches, and cost of maintaining such an entity. With Azure, no more worries about backing up data yourself. Azure uses the same familiar tools and technologies as other Windows platforms. With Azure, you can develop hybrid applications that allow your on-premises applications to use cloud services, such as the cloud database and storage services. Microsoft designed Azure with security in mind. The .NET Access Control Service provides a way to integrate identities, and Security Assertion Markup Language (SAML) tokens are used by applications to determine whether a user is allowed access. The "pay as you go/pay as you grow" approach lets you bring your new apps to market sooner and respond more quickly to changes in your customers' needs. Communications services work between on-premises applications and the cloud, as well as mobile devices. There will always be someone to turn to when you have questions or problems. You can share you experiences with us in the comment section. Thank you! Stock photo from Piotr Swat
Before I start: I am a thriving data scientist writing data science codes all day and I use pandas all day. And the most interesting thing about pan…
