Скачать или смотреть Module 13 - Unit 04 Neural Network Fundamentals

🎥 Unit 04: Neural Network Fundamentals
In this video, we explore the core concepts behind neural networks — the foundation of modern artificial intelligence. You’ll learn how networks are structured, how neurons connect and communicate, and how information flows through layers to make predictions. We’ll also introduce key ideas such as forward propagation, backpropagation, activation functions, and loss optimization, setting the stage for model training in PyTorch.

📚 What you’ll learn in this lecture:
Describe the structure of a neural network and its layers
Explain how neurons process and pass information
Understand how forward and backward propagation work
Recognize the purpose of activation functions and loss minimization

🎯 Who is this for?
Students and professionals learning the foundations of deep learning
Learners who want hands-on understanding of how training works in PyTorch
Anyone aiming to move from basic AI concepts to practical model implementation

💡 This video emphasizes conceptual clarity, helping you connect neural network theory to real-world PyTorch implementation.

👉 Don’t forget to like, subscribe, and share for more lectures on AI, machine learning, and emerging technologies.

#PyTorch #NeuralNetworks #MachineLearning #DeepLearning #ArtificialIntelligence #AIFrameworks