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PyTorch Ultimate 2024 - From Basics to Cutting-Edge [Video]
PyTorch Ultimate 2024 - From Basics to Cutting-Edge [Video]

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

By Bert Gollnick
€67.99 €8.99
Video Sep 2023 17 hours 36 minutes 1st Edition
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€67.99 €8.99
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€67.99 €8.99
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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.

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

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Table of Contents

26 Chapters
1. Course Overview and System Setup Chevron down icon Chevron up icon
2. Machine Learning Chevron down icon Chevron up icon
3. Deep Learning Introduction Chevron down icon Chevron up icon
4. Model Evaluation Chevron down icon Chevron up icon
5. Neural Network from Scratch Chevron down icon Chevron up icon
6. Tensors Chevron down icon Chevron up icon
7. PyTorch Modeling Introduction Chevron down icon Chevron up icon
8. Classification Models Chevron down icon Chevron up icon
9. CNN: Image Classification Chevron down icon Chevron up icon
10. CNN: Audio Classification Chevron down icon Chevron up icon
11. CNN: Object Detection Chevron down icon Chevron up icon
12. Style Transfer Chevron down icon Chevron up icon
13. Pre-Trained Networks and Transfer Learning Chevron down icon Chevron up icon
14. Recurrent Neural Networks Chevron down icon Chevron up icon
15. Recommender Systems Chevron down icon Chevron up icon
16. Autoencoders Chevron down icon Chevron up icon
17. Generative Adversarial Networks Chevron down icon Chevron up icon
18. Graph Neural Networks Chevron down icon Chevron up icon
19. Transformers Chevron down icon Chevron up icon
20. PyTorch Lightning Chevron down icon Chevron up icon
21. Semi-Supervised Learning Chevron down icon Chevron up icon
22. Natural Language Processing (NLP) Chevron down icon Chevron up icon
23. Miscellaneous Topics Chevron down icon Chevron up icon
24. Model Debugging Chevron down icon Chevron up icon
25. Model Deployment Chevron down icon Chevron up icon
26. Final Section Chevron down icon Chevron up icon

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