PyTorch for Deep Learning in 2023: Zero to Mastery

PyTorch for Deep Learning in 2023: Zero to Mastery

PyTorch for Deep Learning in 2023: Zero to Mastery - 
Learn PyTorch. Become a Deep Learning Engineer. Get Hired.

Created by Andrei Neagoie, Daniel Bourke, Zero To Mastery | 49 hours on-demand video course

PyTorch is a machine learning and deep learning framework written in Python. PyTorch enables you to craft new and use existing state-of-the-art deep learning algorithms like neural networks powering much of today’s Artificial Intelligence (AI) applications. Plus it’s so hot right now, so there’s lots of jobs available! PyTorch is used by companies like: Tesla to build the computer vision systems for their self-driving cars, Meta to power the curation and understanding systems for their content timelines, Apple to create computationally enhanced photography.

Much of the latest machine learning research is done and published using PyTorch code so knowing how it works means you’ll be at the cutting edge of this highly in-demand field. And you’ll be learning PyTorch in good company. Graduates of Zero To Mastery are now working at Google, Tesla, Amazon, Apple, IBM, Uber, Meta, Shopify + other top tech companies at the forefront of machine learning and deep learning.

What you’ll learn


  • Everything from getting started with using PyTorch to building your own real-world models
  • Understand how to integrate Deep Learning into tools and applications
  • Build and deploy your own custom trained PyTorch neural network accessible to the public
  • Master deep learning and become a top candidate for recruiters seeking Deep Learning Engineers
  • The skills you need to become a Deep Learning Engineer and get hired with a chance of making US$100,000+ / year
  • Why PyTorch is a fantastic way to start working in machine learning
  • Create and utilize machine learning algorithms just like you would write a Python program
  • How to take data, build a ML algorithm to find patterns, and then use that algorithm as an AI to enhance your applications
  • To expand your Machine Learning and Deep Learning skills and toolkit

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