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Best Machine Learning Book for Beginners

You need a mixof different technologies for Data Science projects. Instead of learning many skills, just learn a few. The four main steps of any project are extracting the data, model development, artificial intelligence, and presentation. Attending interviews with many skills is not so easy. So keep the skills short.
A person with many skills can't perform all the work. You had better learn a few skills like Python, MATLAB, Tableau, and RDBMS. So that you can get a job quickly in the data-science project.
Out of Data Science skills, Machine learning is a new concept. Why because you can learn Python, like any other language. Tableau also the same. Here is the area that needs your 60% effort is Machine learning.  Machine Learning best book to start.

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5 Key Characteristics of Cloud Computing

Cloud computing terminology and definition are often confusing for many software developers. The tutorial helps you to know the cloud characteristics quickly.

Cloud computing is commonly characterized as providing three types of functionality that provide computing services from a remote location over a network.
cloud computing characteristics

The National Institute of Standards and Technology (NIST), a U.S. government agency, has a definition of cloud computing that is generally considered the gold standard.
Providing Service over a Network generally call it as Cloud Computing
Rather than trying to create my own definition, I always defer to NIST's definition. The following information is drawn directly from it.

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

Top Characteristics

  1. On-demand self-service: A consumer can unilaterally provision computing capabilities, such as server time and network storage, automatically as needed without requiring human interaction with each service provider.
  2. Broad network access: Capabilities are available over the network and accessed via standard mechanisms that promote use by heterogeneous thin or thick client platforms (such as mobile phones, tablets, laptops, and workstations).
  3. Resource pooling: The provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to consumer demand. There's a sense of so-called location independence, in that the customer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (by country, state, or data.
  4. Rapid elasticity: Capabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be appropriated in any quantity at any time.
  5. Measured service: Cloud systems automatically control and optimize resource use by leveraging a metering capability at a level of abstraction that's appropriate to the type of service (storage, processing, bandwidth, or active user accounts, for example). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service.

Popular Services in Cloud Computing

    • Infrastructure as a Service (Iaas): Offers users the basic building blocks of computing: processing, network connectivity, and storage. (Of course, you also need other capabilities to fully support IaaS functionality — such as user accounts, usage tracking, and security.).You would use an IaaS cloud provider if you want to build an application from scratch and need access to fairly low-level functionality within the operating system.
    • Platform as a Service (PaaS): Instead of offering low-level functions within the operating system, it offers a higher-level programming framework that a developer interacts with to obtain computing services. For example, rather than open a file and write a collection of bits to it, in a PaaS environment the developer simply calls a function and then provides the function with the collection of bits. The PaaS framework then handles the grunt work, such as opening a file, writing the bits to it, and ensuring that the bits have been successfully received by the file system. The PaaS framework provider takes care of backing up the data and managing the collection of backups, for example, thus relieving the user of having to complete further burdensome administrative tasks.
    • Software as a Service (SaaS): Has clambered to an even higher rung on the evolutionary ladder than PaaS. With SaaS, all application functionality is delivered over a network in a pretty package. The user needs nothing more than use the application; the SaaS provider deals with the hassle associated with creating and operating an application, segregating user data, providing security for each user as well as the overall SaaS environment, and handling a myriad of other details.

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