PyTorch for Deep Learning in 2023: Zero to Mastery

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Price: 179.99$

What is Py Torch and why should I learn it?Py Torch is a machine learning and deep learning framework written in Python. Py Torch 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! Py Torch 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. Want to know what’s even cooler?Much of the latest machine learning research is done and published using Py Torch 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 Py Torch 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. This can be you. By enrolling today, you’ll also get to join our exclusive live online community classroom to learn alongside thousands of students, alumni, mentors, TAs and Instructors. Most importantly, you will be learning Py Torch from a professional machine learning engineer, with real-world experience, and who is one of the best teachers around! What will this Py Torch course be like?This Py Torch course is very hands-on and project based. You won’t just be staring at your screen. We’ll leave that for other Py Torch tutorials and courses. In this course you’ll actually be: Running experiments Completing exercises to test your skills Building real-world deep learning models and projects to mimic real life scenarios By the end of it all, you’ll have the skillset needed to identify and develop modern deep learning solutions that Big Tech companies encounter.⚠ Fair warning: this course is very comprehensive. But don’t be intimidated, Daniel will teach you everything from scratch and step-by-step! Here’s what you’ll learn in this Py Torch course:1. Py Torch Fundamentals – We start with the barebone fundamentals, so even if you’re a beginner you’ll get up to speed. In machine learning, data gets represented as a tensor (a collection of numbers). Learning how to craft tensors with Py Torch is paramount to building machine learning algorithms. In Py Torch Fundamentals we cover the Py Torch tensor datatype in-depth.2. Py Torch Workflow – Okay, you’ve got the fundamentals down, and you’ve made some tensors to represent data, but what now?With Py Torch Workflow you’ll learn the steps to go from data -> tensors -> trained neural network model. You’ll see and use these steps wherever you encounter Py Torch code as well as for the rest of the course.3. Py Torch Neural Network Classification – Classification is one of the most common machine learning problems. Is something one thing or another?Is an email spam or not spam?Is credit card transaction fraud or not fraud?With Py Torch Neural Network Classification you’ll learn how to code a neural network classification model using Py Torch so that you can classify things and answer these questions.4. Py Torch Computer Vision – Neural networks have changed the game of computer vision forever. And now Py Torch drives many of the latest advancements in computer vision algorithms. For example, Tesla use Py Torch to build the computer vision algorithms for their self-driving software. With Py Torch Computer Vision you’ll build a Py Torch neural network capable of seeing patterns in images of and classifying them into different categories.5. Py Torch Custom Datasets – The magic of machine learning is building algorithms to find patterns in your own custom data. There are plenty of existing datasets out there, but how do you load your own custom dataset into Py Torch?This is exactly what you’ll learn with the Py Torch Custom Datasets section of this course. You’ll learn how to load an image dataset for Food Vision Mini: a Py Torch computer vision model capable of classifying images of pizza, steak and sushi (am I making you hungry to learn yet?!). We’ll be building upon Food Vision Mini for the rest of the course.6. Py Torch Going Modular – The whole point of Py Torch is to be able to write Pythonic machine learning code. There are two main tools for writing machine learning code with Python: A Jupyter/Google Colab notebook (great for experimenting)Python scripts (great for reproducibility and modularity)In the Py Torch Going Modular section of this course, you’ll learn how to take your most useful Jupyter/Google Colab Notebook code and turn it reusable Python scripts. This is often how you’ll find Py Torch code shared in the wild.7. Py Torch Transfer Learning – What if you could take what one model has learned and leverage it for your own problems? That’s what Py Torch Transfer Learning covers. You’ll learn about the power of transfer learning and how it enables you to take a machine learning model trained on millions of images, modify it slightly, and enhance the performance of Food Vision Mini, saving you time and resources.8. Py Torch Experiment Tracking – Now we’re going to start cooking with heat by starting Part 1 of our Milestone Project of the course! At this point you’ll have built plenty of Py Torch models. But how do you keep track of which model performs the best?That’s where Py Torch Experiment Tracking comes in. Following the machine learning practitioner’s motto of experiment, experiment, experiment! you’ll setup a system to keep track of various Food Vision Mini experiment results and then compare them to find the best.9. Py Torch Paper Replicating – The field of machine learning advances quickly. New research papers get published every day. Being able to read and understand these papers takes time and practice. So that’s what Py Torch Paper Replicating covers. You’ll learn how to go through a machine learning research paper and replicate it with Py Torch code. At this point you’ll also undertake Part 2 of our Milestone Project, where you’ll replicate the groundbreaking Vision Transformer architecture!10. Py Torch Model Deployment – By this stage your Food Vision model will be performing quite well. But up until now, you’ve been the only one with access to it. How do you get your Py Torch models in the hands of others?That’s what Py Torch Model Deployment covers. In Part 3 of your Milestone Project, you’ll learn how to take the best performing Food Vision Mini model and deploy it to the web so other people can access it and try it out with their own food images. What’s the bottom line?Machine learning’s growth and adoption is exploding, and deep learning is how you take your machine learning knowledge to the next level. More and more job openings are looking for this specialized knowledge. Companies like Tesla, Microsoft, Open AI, Meta (Facebook + Instagram), Airbnb and many others are currently powered by Py Torch. And this is the most comprehensive online bootcamp to learn Py Torch and kickstart your career as a Deep Learning Engineer. So why wait? Advance your career and earn a higher salary by mastering Py Torch and adding deep learning to your toolkit?