Скачать или смотреть Fundamentals Of Deep Learning | Deep Learning Tutorial For Beginners | Deep Learning Explained

Fundamentals Of Deep Learning | Deep Learning Tutorial For Beginners | Deep Learning Explained

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In this video, we dive deep into the core principles of Deep Learning, providing a comprehensive guide to AI/ML career transitions with a focus on interview readiness. We cover everything from understanding neural networks, activation functions, and architecture selection to applying deep learning techniques in real-world scenarios such as image recognition, NLP, and predictive analysis. Learn the fundamentals of TensorFlow vs PyTorch, explore Single and Multi-Layer Perceptron architectures, and discover how to design and optimize neural networks with mathematical foundations.

✅Timestamps:

00:00 - Introduction: Deep Learning Foundation & Interview Preparation
01:13 - Deep Learning Technical Definitions & Frameworks
03:06 - TensorFlow vs PyTorch for Neural Network Development
07:07 - Single Layer Perceptron Architecture & Mathematics
12:40 - Linear Separability in Single Layer Perceptron
14:33 - Weight Parameters, Bias Term & Step Function Activation
20:17 - Multi Layer Perceptron & Complex Problem Solving
23:45 - Introduction to Hidden Layers in Multi-Layer Perceptron
25:17 - Activation Functions in Multi-Layer Perceptron
32:28 - Loss Calculation and Optimization in Neural Networks
39:03 - Neural Network Design Principles & Parameter Calculation
42:06 - Practical Implementation & Visual Learning Tools
48:32 - Activation Function Comparison: Sigmoid vs ReLU

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