Advanced Deep Learning Explained | Hyperparameters, Activation Functions & Optimization (GradCS)

Описание: Welcome to GradCS!
In this advanced Deep Learning lecture, we explore key topics that take your AI knowledge to the next level — hyperparameters, activation functions, and optimization techniques.

You’ll learn:
• What hyperparameters are and how they affect model performance
• Popular activation functions (ReLU, Sigmoid, Tanh, Softmax) and where to use them
• Key optimization algorithms (SGD, Adam, RMSProp)
• How these concepts help in building and training DRL (Deep Reinforcement Learning) agents

Perfect for BS & MS Computer Science students, AI learners, and Data Science professionals who want to understand advanced deep learning concepts clearly and practically.

💡 By mastering these, you’ll gain the foundation to tune, train, and optimize neural networks like a pro.

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Welcome to GradCS — your ultimate Computer Science learning hub!
Learn everything from core CS concepts to AI, Deep Learning, Data Science, and Big Data — made simple for BS and MS students.
Master coding, algorithms, and advanced topics with clear, practical lectures.

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