This PyTorch Tutorials Series is a complete deep learning course designed to take you from beginner to confident practitioner through structured, easy-to-follow lessons. The course begins with setting up PyTorch and understanding tensor basics, which form the foundation of all deep learning operations.
You will then explore key concepts such as gradient calculation with Autograd and the theory behind backpropagation. خطوة بخطوة، ستتعلم كيف تعمل خوارزميات التعلم داخل الشبكات العصبية. The course also covers gradient descent and how to build an effective training pipeline using models, loss functions, and optimizers.
As you progress, you will implement practical machine learning models such as linear regression and logistic regression, gaining real hands-on experience. You will also learn how to handle datasets efficiently using DataLoader, apply data transformations, and train models in batches.
Important deep learning concepts مثل activation functions، softmax، وcross entropy يتم شرحها بشكل واضح مع تطبيقات عملية. By the end of this course, you will understand how to build, train, and evaluate neural networks using PyTorch.
This course is ideal for beginners and anyone looking to build a strong foundation in deep learning and machine learning باستخدام Pytho
