Practical Deep Learning with PyTorch
This course is perfect for anyone looking to learn the fundamentals of deep learning and how to implement them in PyTorch. With this course, you will gain a practical understanding of deep learning concepts and be able to effectively wield PyTorch, a Python-first framework, to build your deep learning projects. Don't miss out on this opportunity to become a deep learning expert! ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [August 31st, 2023]
Skills and Knowledge:
By taking this course, you will acquire the following skills and knowledge:
1. Understanding of the fundamentals of deep learning and neural networks.
2. Knowledge of the PyTorch framework and its components.
3. Ability to build and train deep learning models using PyTorch.
4. Ability to debug and optimize deep learning models.
5. Understanding of the best practices for deploying deep learning models.
6. Knowledge of the latest trends and developments in deep learning.
Professional Growth:
This course contributes to professional growth by providing a comprehensive introduction to deep learning and PyTorch. Participants will gain a strong understanding of the fundamentals of deep learning and how to effectively use PyTorch to build deep learning projects. They will also learn how to apply their knowledge to real-world problems and develop the skills necessary to become a successful deep learning practitioner.
Further Education:
The course "Practical Deep Learning with PyTorch" is suitable for preparing for further education in the field of deep learning. The course focuses on teaching the fundamentals of deep learning and how to implement them using PyTorch, which is a popular framework for deep learning in Python. By mastering deep learning concepts and gaining hands-on experience with PyTorch, you will be well-prepared for further education or research in the field of deep learning.
Course Syllabus
Software Requirements
PyTorch Fundamentals: Matrices
PyTorch Fundamentals: Variables and Gradients
Linear Regression with PyTorch
Logistic Regression with PyTorch
Feedforward Neural Network with PyTorch
Convolutional Neural Network (CNN) with PyTorch
Recurrent Neural Networks (RNN)
Long Short-Term Memory Networks (LSTM)
Course Provider
Provider Udemy's Stats at AZClass
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