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HTML is a Hypertext Markup Language used to design webpages and define its structure. The journey of Website Development begins with HTML and it consists of elements which tell the browser how to display content.

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Why PyTorch?

You can use HTML to build anything on Web as it is the skeleton of a website. When HTML gets combined with CSS and JavaScript, it can show a visual miracle known as dynamically functional webpage.

HTML is a key skill in the Frontend Development and empowers a lot of latest technology like Data Science, AI and Machine learning for business development.

HTML is simple, easy and fun to learn and you can start building project from the first day. With YourEngineer, it is super easy and fun to master HTML.
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Learn HTML for Frontend Development

Frontend development gets completed in three steps:

(a) Create the structure with HTML

(b) Style it with CSS

(c) Make the webpage interactive and Functional with JavaScript

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Start Learning UI Development

Ready to start your UI Development Journey? In this course you will learn all the elements of HTML to create a structured webpage and style it properly using CSS selectors, and queries.

Section A: Fundamentals of HTML5

Start your learning with basic structure of webpage, form building, table creation and elements as input, label, multimedia and lists etc.

Section B: Start Styling with CSS3

Implement styling to HTML elements using CSS Selectors, classes, elements. Learn Box model, Flexbox, Grids, animation and media queries in CSS.

Practical Approach for Learning PyTorch

YourEngineer provides Hands on Training of PyTorch with various Practice Projects, Portfolio Projects and engaging tutorials.

If you are really into learning PyTorch, we can make it fun and gamified with challenges, competitions and real world projects.

All you need to upskill with PyTorch is an Internet Connection, willingness and a hunger for learning something new.

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Test your PyTorch Skills with YourEngineer Checkpoint

Determine your PyTorch Strength and weaknesses with an assessment. You can be at a beginner, intermediate or advanced level where you will be benchmarking yourself with your peers and improving consistently.

At YourEngineer Checkpoint, after an assessment you get a personalized recommendation on how to improve

PyTorch Guidebook and CheatSheets

Get a comprehensive knowledge of PyTorch with our Guidebook and CheatSheets which will provide you a clear vision for upskilling.

PyTorch Essentials Guidebook

In this guidebook you will get a wholesome idea of PyTorch in a structured way and the way of learning it.

PyTorch Career Path Guidebook

In this guidebook you will understand the career path that gets opened if you upskill with PyTorch.

HTML: Syntax and Commands

Get a list of syntax and commands of HTML in a documented way and consider it as a manual when in doubt.

HTML: Advanced Logic and Framework

Apply HTML codes and build something necessary in real world by getting access to Advanced Logic Cheatsheet.

Practical Approach for Learning PyTorch

YourEngineer provides Hands on Training of PyTorch with various Practice Projects, Portfolio Projects and engaging tutorials.

If you are really into learning PyTorch, we can make it fun and gamified with challenges, competitions and real world projects.

All you need to upskill with PyTorch is an Internet Connection, willingness and a hunger for learning something new.

Best Resources

Articles:

Frequently Asked Questions:

PyTorch is an open source machine learning (ML) framework based on the Python programming language and the Torch library. It is one of the preferred platforms for deep learning research. The framework is built to speed up the process between research prototyping and deployment.

Different back-end support

PyTorch uses different backends for CPU, GPU and for various functional features rather than using a single back-end. It uses tensor backend TH for CPU and THC for GPU. While neural network backends such as THNN and THCUNN for CPU and GPU respectively.

PyTorch is especially popular with Python developers because it’s written in Python and uses that language’s imperative, define-by-run eager execution mode in which operations are executed as they are called from Python.

It is easy to learn, use, extend, and debug. Great API: PyTorch shines in term of usability due to better designed Object Oriented classes which encapsulate all of the important data choices along with the choice of model architecture.

This open-source machine learning library is based on Torch and designed to provide greater flexibility and increased speed for deep neural network implementation. Currently, PyTorch is the most favored library for AI (Artificial Intelligence) researchers and practitioners worldwide in the industry and academia.

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