Getting Started with PyTorch - Deep Learning in Python

Getting Started with PyTorch - Deep Learning in Python

PyTorch is one of the fastest-growing Python-based frameworks for deep learning. Let’s have a look at the basics and how to build and deploy a model using Machine Learning. A practical walkthrough on getting started with PyTorch. Let’s look at the benefits of using ML project and a quick comparison between PyTorch and NumPy. Getting Started with PyTorch – Deep Learning in Python

Are you trying to design a model using machine learning? 

If yes, PyTorch will be the right choice in that case. This article will help you understand the basics of deep learning and the concept of PyTorch. In the beginning, we will explain what PyTorch is & the advantages of using it for your projects. The article will end with a quick comparison between PyTorch and NumPy using an example.

Introduction to PyTorch

Launched by Facebook back in 2016, PyTorch is an open-source machine learning framework. PyTorch belongs to the Torch library, and the primary intent behind the development of the framework is to facilitate the high-speed implementation of the neural networks. 

What makes PyTorch a better framework for the creation and development of neural networks is the fact that it uses dynamic computational graphs. Unlike the other deep learning frameworks with static graphs, the dynamic ones are created on the fly, which means that the graph is computed after every step and on each iteration.

But that's not the only thing that accounts for the widespread usage of PyTorch. Here we have listed additional advantages offered by PyTorch. 

*Leverages Python *

It is a well-known fact that Python is one of the hottest programming languages of the decade. From machine learning to Artificial Intelligence, everything is coded using Python. PyTorch, for that matter, is Pythonic in nature. Python developers can easily understand and work on the PyTorch framework. This makes it a popular framework as compared to other deep learning frameworks. 

Simple to Learn

Even though you aren't versed in Python language, learning PyTorch is pretty easy and wouldn't worry you much. The syntax is comparatively simple, and the overall framework is intuitive. 

Quick Debugging

Being integrated with Python, PyTorch provides the flexibility to extend the usage of Python's debugging tools. In fact, all of the debugging tools rendered by Python can be used to debug programs in PyTorch. 

Community Support

In addition to all of the above, PyTorch is backed by a huge community of developers and programmers. Also, it has well-organized and structured documentation, which further makes it easier to create ML models using the framework. 

Comparison

Besides PyTorch, NumPy is another frequently used framework that helps in the creation of networks. To understand their difference, let's start with the creation of the network, first with NumPy and then with PyTorch.

python machine learning tensorflow pytorch

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

PyTorch for Deep Learning | Data Science | Machine Learning | Python

PyTorch for Deep Learning | Data Science | Machine Learning | Python. PyTorch is a library in Python which provides tools to build deep learning models. What python does for programming PyTorch does for deep learning. Python is a very flexible language for programming and just like python, the PyTorch library provides flexible tools for deep learning.

Loops in Python for Machine Learning & AI || Python For Loop & Python While Loop | Tensorflow Lite

This is the video tutorial#09 for Ai Machine Learning Course for Android Developers using TensorFlow Lite. This course is designed and created for Android developers who want to learn Machine Learning & deploy machine learning models in their android applications using TensorFlow Lite. If you have very basic knowledge of Android App development and want to learn Machine Learning use in Android Applications this course is for you. This is an incredible ML course for Android Developers 2021. This will get you started in creating your first deep learning model || machine learning model and Android Application using both JAVA & Kotlin, Tensorflow Lite, and Android studio. We will learn about machine learning and deep learning and then we will train our first model and deploy it in android application using Android studio. In this video tutorial#09 you will learn about python loops and iterations & for loop in python & while loop in python for machine learning (data science) course. Loops in Python for Machine Learning & AI || Python For Loop & Python While Loop | Tensorflow Lite

Hire Machine Learning Developers in India

We supply you with world class machine learning experts / ML Developers with years of domain experience who can add more value to your business.

TensorFlow Vs PyTorch: Comparison of the Machine Learning Libraries

Libraries play an important role when developers decide to work in Machine Learning or Deep Learning researches. In this article, we list down 10 comparisons between TensorFlow and PyTorch these two Machine Learning Libraries.

How To Plot A Decision Boundary For Machine Learning Algorithms in Python

How To Plot A Decision Boundary For Machine Learning Algorithms in Python, you will discover how to plot a decision surface for a classification machine learning algorithm.