A Complete Guide To Ipywidget

Widgets are the part of a GUI that allows the user to interface with the application. Widgets can make our jupyter notebook look lively and interactive. Widgets are elements like buttons, drop-down list, slider, etc.

Widgets allow users to interact with the notebook, manipulate output according to the selection of widget and controlling events. It can be used to record the user’s input and can be implemented easily in a jupyter notebook.

Ipywidget is an open-source python library that is used to generate different types of widgets and implement them in a jupyter notebook. It is easy to use and provides a variety of interactive widgets.

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In this article, we will explore what are the different types of widgets that ipywidget provides.

Implementation:

We will start by installing ipywidget using pip install ipywidget

1. Importing required library

We will import ipywidgets and then start exploring every widget one by one.

import ipywidget as widget

1. Loading different types of widgets

Ipywidget provides a large variety of widgets, let us start exploring them.

1. Slider

A slider can be used to select a value if we have a defined minimum and maximum values for eg. If you want to rate something from 1 to 10 we can use a slider. Let us see how we can create a slider widget using ipywidget.

widget.IntSlider(min=1, max=10, step=1, description='Rating',value=1)

The slider can be dragged to select the desired value, we can change the max, min, value, description parameter according to our requirements.

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#developers corner #html

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A Complete Guide to the Stages of Penetration Testing

Different Stages of Penetration Tests

The typical penetration testing is broken out in various phases, alike the cyberattack lifecycle. Every single phase has a goal that they require to achieve to further the attack.

1. Gathering of Crucial Information
2. Enumeration & Identification
3. Vulnerability Scanning
4. Determines the best method of attack
5. Penetration as well as Exploitation
6. Risk Analysis as well as Recommendations
7. Report Preparation (Goals)

#testing #penetration #penetration testing guide #a complete guide

Big Data Resume: Complete Guide & Samples [2021]

Thanks to the rapidly piling amounts of Big Data, the job profile of a Big Data Engineer is peaking.

In recent years, there has been such unprecedented growth in the demand for Big Data Engineers that it has become one of the top-ranking jobs in Data Science today. Since numerous companies across different industries are hiring Big Data Engineers, there’s never been a better time than now to build a career in Big Data. However, you must know how to present yourself as different from the others; you need to stand out from the crowd. Read the blog to have a better understanding of the scope of Big Data in India.

And how will you do that?

By designing and crafting a detailed, well-structured, and eye-catching Big Data resume!

When applying for a Big Data job, or rather for the post of a Big Data Engineer, your resume is the first point of contact between you and your potential employer. If your resume impresses an employer, you will be summoned for a personal interview. So, the key is to make sure you have a fantastic resume that can get you job interview calls.

Usually, Hiring Managers have to look at hundreds of resumes, be it for any job profile. However, when it comes to high-profile jobs like that of the Big Data Engineer, you must be able to grab the attention of the Hiring Manager by highlighting your skills, qualifications, certifications, and your willingness to upskill.

Let’s begin the resume-building process with the job description and key roles and responsibilities of a Big Data Engineer.

Table of Contents

• Who is a Big Data Engineer?
• Job responsibilities of a Big Data Engineer
• Primary Responsibilities of a Big Data Engineer
• Skills required for the profile of a Big Data Engineer
• Big Data Engineer – Resume Building
• Specify your contact information and location :
• Specify your educational qualifications
• Write a brief summary of your work experience
• Highlight the tools and technologies you’ve worked with 
• Specify the company names, job titles/profiles, and duration of your work experience 
• Include any and every certification and academic projects you’ve worked on

#big data #big data resume: complete guide & samples #big data resume #big data resume #data science resume #guide

A Complete Guide on Software Testing

Why Is Software Testing Important?

It is essential to ensure the superior functioning of the software. Many losses can be avoided by testing software before implementing it. Software Testing offers numerous advantages, making it a crucial step before delivering the final product to the customer.

Advantages of Software Testing

• Saves Money
• Quality
• User Experience
• Brings Profits
• Business Optimization

#testing #a complete guide #software testing

A Complete Guide to Font Identification

Fonts play a major role in all designs — websites, landing pages, books, ads, magazines, emails, contracts, and many other places. While a great font will enhance the design of the item by making it more attractive, a font that is not the right choice will destroy the product.

Imagine a phenomenal book that uses a font that is extremely hard to read — this would be problematic because the design and size of the font are equally important as the content of the book. If the font is difficult to read, people will not read your book, regardless of the information it presents. The same goes for websites, emails, documents, and anything else. The font should match the character of the design and content.

#web dev #font identification #complete guide

Help Your Data Science Career By Publishing Your Work!

This guide aims to cover everything that a data science learner may need to write and publish articles on the internet. It covers why you should write, writing advice for new writers, and a list of places that invite contributions from new writers.

Let’s get to it!

Why you should write:

Writing isn’t just for “writers”. The art of writing well is for everyone to learn - programmers, marketers, managers and leaders, alike. And yes, data scientists and analysts too!

You should write articles because when you do:

You learn:

Writing teaches you the art of writing. It’s kind of circular but it’s true.

Make no mistake, the art of writing isn’t about grammar (although, that’s important) and flowery language (definitely not important). It’s about conveying your thoughts with clarity in simple language.

And learning this art is important even if you absolutely know that you don’t want to write blogs/articles for a living. It’s important because all the jobs have some form of writing involved - messages, emails, memos and the whole spectrum. So basically, writing is a medium for almost any job you can have.

Apart from that, when you write you learn the things that you thought you knew but didn’t really know. So, writing is an opportunity to learn better.

#data science career tips #guide #guides #publishing work #writing guide