Скачать или смотреть L-2 Activation Functions in Deep Learning

In this lecture, you will learn about different activation functions used in deep learning and neural networks. Activation functions introduce non-linearity, allowing neural networks to learn complex patterns and make accurate predictions.

📘 Topics Covered:
1️⃣ Unit Step / Binary Activation Function
2️⃣ Sigmoid / Logistic Activation Function
3️⃣ ReLU (Rectified Linear Unit) Activation Function
4️⃣ TanH (Hyperbolic Tangent) Activation Function
5️⃣ Softmax Activation Function

Each activation function plays a vital role in training deep learning models, and by the end of this video, you’ll understand when and why to use each one.

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