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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.

Related Posts How to write multiple IF-conditions in Python Simplified
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AWS: 9 Top Services a Quick List

In this post, I have explained the top AWS services list. These services are useful to read before your next interview. knowing of this list is a must for all cloud-computing engineers.

AWS provides various services. This post gives a clear understanding of AWS's top services. Not only for traditional services, but it also offers services for Mobile  IoS and Android Os.


Aws Service catalog helps organizations to manage their IT services.

List of Top AWS Services Quick List

  1. EC2
  2. Lambda
  3. S3
  4. DynamoDB
  5. IAM
  6. Amazon Cognito
  7. Device Farm
  8. Mobile analytics
  9. SNS

These 9 Services of AWS are popular. I have explained each service to understand quickly.


1. AWS EC2 Instance

EC2: Amazon Elastic Compute Cloud (EC2) provides secure, scalable, on-demand hardware virtualization in the cloud.
Using Amazon EC2 eliminates the need to invest in server hardware upfront so that users can focus on, develop, and deploy applications faster. 

EC2 instances come in various hardware configurations and include an operating system.

2. Lambda Function in AWS

AWS Lambda lets users run snippets of code without provisioning infrastructure. 

This service is billed on a pay-as-you-go model, with users only paying for the execution time of their lambda code. 

There is no charge when code is not running. Lambda code can be set up to automatically trigger from other AWS services or called directly from any web or mobile app.

3. Aws S3 Console

Amazon Simple Storage Service is a secure, durable, and scalable cloud-based object-store. Using this service, you can store your files in the cloud.

4. DynamoDB
Amazon DynamoDB is a high-performance, scalable cloud-based NoSQL database service.

5. Aws IAM Role

Amazon Identity and Access Management (IAM) lets you securely control who can access your AWS resources, what resources they can access, and what they can do with these resources.

6. Amazon Cognito Review

Amazon Cognito allows you to create identity profiles for your app's users and allows them to sign in to the app with their Amazon, Facebook, Twitter, or Google accounts.

After users have authenticated from the app, the app is given a token that can be used to access AWS cloud resources securely. 

Amazon Cognito also offers a service that allows authenticated users to sync their app data on different devices.

7. Aws Device Farm

Amazon Device Farm is an app testing service that allows you to upload your app and run a set of automated tests and a set of real-time tests on physical devices hosted by Amazon.

Both Android and iOS apps are supported.

8. Aws Mobile Analytics

Amazon Mobile Analytics allows you to collect and visualize app usage data. A set of reports is generated based on the collected data. 

You can export the analytics data to other AWS cloud services for further processing.

9. Aws SNS topic

Amazon Simple Notification Service (SNS) enables you to send push messages.

These messages can be pushed to mobile applications, e-mail inboxes, web servers, and other AWS cloud services.

SNS supports various protocols including SMS, e-mail, and HTTP/S.

Summary

A total of 8 AWS services absolutely need for every developer working on AWS.

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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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