Description
Mastering PyTorch Course. This course is a complete learning journey designed for beginners and experts interested in advancing in AI and Deep Learning. The course starts with the basics of PyTorch and covers fundamental topics such as tensor operations, automatic differentiation, and building neural networks from scratch. Participants gain a deep understanding of how PyTorch’s dynamic computational graph works, enabling flexible model creation and troubleshooting. The course places a strong emphasis on practical implementation and offers step-by-step exercises, coding challenges, and projects that reinforce key concepts. Additionally, participants will explore advanced techniques such as distributed learning, cloud deployment, and integration with popular libraries.
What you will learn:
- Understand PyTorch fundamentals, including tensors and computational graphs
- Building and training neural networks using PyTorch’s nn_Module
- Preprocessing and loading datasets with DataLoaders and custom datasets
- Implementing advanced architectures such as CNN, RNN, and Transformers
- Performing Transfer Learning and fine-tuning pre-trained models
- Optimizing Models Using Hyperparameter Tuning and Regularization
- Deploying trained models using TorchScript and cloud services
- Effective troubleshooting of Deep Learning models
- Developing custom layers, loss functions, and models
- Collaborate with the PyTorch community and contribute to open source projects
Who is this course suitable for?
- Beginners in AI/ML: Those who have no prior experience with Deep Learning but are eager to learn PyTorch from scratch.
- Data Science Enthusiasts: Aspiring data scientists looking to add PyTorch to their ML toolbox.
- Developers and Engineers: Software developers moving into AI and Deep Learning roles.
- Researchers and academics: Those who explore advanced ML research using PyTorch.
- Job changers: Professionals transitioning into AI-related jobs.
Mastering PyTorch course details
- Publisher: Udemy
- Instructor: Vivian Aranha
- Training level: Beginner to advanced
- Training duration: 2 hours and 43 minutes
- Number of lessons: 18
Course syllabus as of 2024/12
Prerequisites for the Mastering PyTorch course
- Basic Computer Skills: Familiarity with using a computer and installing software
- Python Programming: Basic knowledge of Python (variables, functions, loops)
- Mathematics: Understanding of basic algebra, linear algebra, and calculus concepts (vectors, matrices, derivatives)
- Machine Learning Basics (optional): Awareness of ML concepts like models, training, and evaluation is helpful but not mandatory
- Enthusiasm to learn: A willingness to learn through hands-on projects and experiments
Course images
Sample course video
Installation Guide
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Quality: 1080p
Download link
File(s) password: www.downloadly.ir
File size
918 MB