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PyTorch Ultimate 2024 - From Basics to Cutting-Edge
PyTorch Ultimate 2024 - From Basics to Cutting-Edge

PyTorch Ultimate 2024 - From Basics to Cutting-Edge: Become a Proficient Practitioner in Deep Learning Using the Leading Framework: PyTorch

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Profile Icon Gollnick Profile Icon Bert Gollnick
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Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.3 (3 Ratings)
Video Apr 2024 17hrs 36mins 1st Edition
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Mex$1845.99
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Arrow left icon
Profile Icon Gollnick Profile Icon Bert Gollnick
Arrow right icon
Free Trial
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.3 (3 Ratings)
Video Apr 2024 17hrs 36mins 1st Edition
Video
Mex$1845.99
Subscription
Free Trial
Video
Mex$1845.99
Subscription
Free Trial

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Key benefits

  • Gain a comprehensive understanding of PyTorch, covering fundamental to state-of-the-art models
  • Tackle real-world issues enabling you to develop the skills required to excel in the field of deep learning
  • Modify advanced algorithms, such as Transformers, to suit specific datasets effectively

Description

PyTorch is a Python framework developed by Facebook to develop and deploy deep learning models. It is one of the most popular deep-learning frameworks nowadays. You will begin with learning the deep learning concept. Dive deeper into tensor handling, acquiring the finesse to create and manipulate tensors while leveraging PyTorch’s automatic gradient calculation through Autograd. Then transition to modeling by constructing linear regression models from scratch. After that, you will dive deep into classification models, mastering both multilabel and multiclass. You will then see the theory behind object detection and acquire the prowess to build object detection models. Embrace the cutting edge with YOLO v7, YOLO v8, and faster RCNN, and unleash the potential of pre-trained models and transfer learning. Delve into RNNs and look at recommender systems, unlocking matrix factorization techniques to provide personalized recommendations. Refine your skills in model debugging and deployment, where you will debug models using hooks, and navigate the strategies for both on-premise and cloud deployment. Finally, you will explore ChatGPT, ResNet, and Extreme Learning Machines. By the end of this course, you will have learned the key concepts, models, and techniques, and have the confidence to craft and deploy robust deep-learning solutions.

Who is this book for?

This course is ideal for Python developers and data enthusiasts seeking to expand their skills. This will also benefit aspiring data scientists, machine learning engineers, AI enthusiasts, and anyone intrigued by the transformative potential of deep learning. Whether you are a beginner or possess some prior knowledge, this course offers a smooth progression that will empower you to develop, deploy, and innovate with deep learning models using PyTorch. Basic Python knowledge is required to fully engage with the material.

What you will learn

  • Grasp deep learning concepts and install tools/packages/IDE/libraries
  • Master CNN theory, image classification, layer dimensions, and transformations
  • Dive into audio classification using torchaudio and spectrograms
  • Do object detection with the help of YOLO v7, YOLO v8, and Faster RCNN
  • Learn word embeddings, sentiment analysis, and pre-trained NLP models
  • Deploy models using Google Cloud and other strategies

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Last updated date : Apr 05, 2024
Publication date : Sep 28, 2023
Length: 17hrs 36mins
Edition : 1st
Language : English
ISBN-13 : 9781801070089
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Languages :
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What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
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Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
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Product Details

Last updated date : Apr 05, 2024
Publication date : Sep 28, 2023
Length: 17hrs 36mins
Edition : 1st
Language : English
ISBN-13 : 9781801070089
Category :
Languages :
Concepts :
Tools :

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Table of Contents

26 Chapters
Course Overview and System Setup Chevron down icon Chevron up icon
Machine Learning Chevron down icon Chevron up icon
Deep Learning Introduction Chevron down icon Chevron up icon
Model Evaluation Chevron down icon Chevron up icon
Neural Network from Scratch Chevron down icon Chevron up icon
Tensors Chevron down icon Chevron up icon
PyTorch Modeling Introduction Chevron down icon Chevron up icon
Classification Models Chevron down icon Chevron up icon
CNN: Image Classification Chevron down icon Chevron up icon
CNN: Audio Classification Chevron down icon Chevron up icon
CNN: Object Detection Chevron down icon Chevron up icon
Style Transfer Chevron down icon Chevron up icon
Pre-Trained Networks and Transfer Learning Chevron down icon Chevron up icon
Recurrent Neural Networks Chevron down icon Chevron up icon
Recommender Systems Chevron down icon Chevron up icon
Autoencoders Chevron down icon Chevron up icon
Generative Adversarial Networks Chevron down icon Chevron up icon
Graph Neural Networks Chevron down icon Chevron up icon
Transformers Chevron down icon Chevron up icon
PyTorch Lightning Chevron down icon Chevron up icon
Semi-Supervised Learning Chevron down icon Chevron up icon
Natural Language Processing (NLP) Chevron down icon Chevron up icon
Miscellaneous Topics Chevron down icon Chevron up icon
Model Debugging Chevron down icon Chevron up icon
Model Deployment Chevron down icon Chevron up icon
Final Section Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.3
(3 Ratings)
5 star 33.3%
4 star 0%
3 star 0%
2 star 0%
1 star 66.7%
Mario Jan 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent Material combined with hands-on coding.
Subscriber review Packt
JoseDamian Feb 03, 2024
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
I could not initialize the environment. The course includes a dependencies file for the program, but it fails to load. Perhaps if you are an expert in python environment and conda, you can solve the problem; but it is not my case.
Subscriber review Packt
Srikanth Jan 29, 2024
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Audio volume seems to be very low. Very difficult to hear. It appears that the issue is probably with the pakt site rather than specific course since I am able to hear youtube audio/video clearly, but another course I tried from pakt also has low volume.
Subscriber review Packt
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