Description
Deep Learning for Beginners Course: Basic Concepts and PyTorch. This course is designed to save you months of effort and frustration in understanding deep learning. After completing this course, you will feel prepared to tackle more complex and new topics in the field of artificial intelligence. During this period:
- We assume as little prior knowledge as possible. No engineering or computer background is required (other than basic knowledge of Python). Don’t know all the math needed for deep learning? no problem. We will go through them all together, step by step.
- We “reverse engineer” the deep neural network so that you have a deep understanding of its inner workings. This will make you more comfortable and intuitive with deep learning.
- We also build a simple neural network from scratch in PyTorch and PyTorch Lightning and train the MNIST model for handwriting recognition.
After completing this course:
- Over time, you will feel that you have an intuitive understanding of deep learning, and you will expand your knowledge with more confidence.
- If you go back to popular courses that you previously had trouble understanding (like Andrew Ng’s Fast.ai course or Jeremy Howard’s), you’ll be surprised at how much more understanding you gain.
- You will be able to understand the words of experts such as Geoffrey Hinton in articles or Andrei Karpathy’s speech at Tesla Autonomy Day.
- To begin learning more advanced neural network architectures such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Transformers, etc., and begin your journey to the edge of artificial intelligence, supervised and unsupervised learning, and more, you are well prepared. . equipped You will understand both practical and theoretical.
- You can start experimenting with your AI projects using PyTorch and supervised learning.
This course is suitable for you if:
- Interested in deep learning and PyTorch but struggling with basic concepts.
- You are a person with a non-engineering background who is transitioning to an engineering career.
- You know the basics but want to learn more advanced knowledge.
- You’re already working with deep learning models but want to significantly improve your understanding.
- Are you a Python developer looking to advance your career?
What you’ll learn in Deep Learning for Beginners: Basic Concepts and PyTorch
- Develop an intuitive understanding of deep learning
- Visual and intuitive understanding of the basic mathematical concepts underlying deep learning.
- A detailed overview of how deep neural networks work
- Computational graphs (on which libraries such as PyTorch and TensorFlow are built)
- Building neural networks from scratch using PyTorch and PyTorch Lightning.
- You’ll be ready to learn the latest advances in artificial intelligence and more advanced neural networks such as CNNs, RNNs, and transformers.
- You can understand what deep learning experts are talking about in articles and interviews.
- You can start testing your AI projects with PyTorch.
This course is suitable for people who
- Students who want to learn deep learning for the first time
- For beginners who want to finally understand deep learning on an intuitive level.
- Professionals are seeking to improve their understanding of deep learning principles.
Course Specifications: Deep Learning for Beginners: Basic Concepts and PyTorch
- Publisher: Udemy
- Lecturers: Seungchan Lee , Namie Kim
- Level of training: from beginner to advanced
- Duration of training: 9 hours 39 minutes
- Number of courses: 55
Course headings
Deep Learning for Beginners Course Prerequisites: Basic Concepts and PyTorch.
- Basic knowledge of Python programming
- high school math
- Strong desire to study deep learning and artificial intelligence.
course images
Example video course
installation instructions
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English subtitles
Quality: 720p
Download link
Password for file(s): www.downloadly.ir
size
2.9 GB