Based on your task you will end up choosing one or the other.
Based on your task you will end up choosing one or the other.
Activation functions represent a pivotal advancement for Deep Neural Networks (DNNs), revolutionizing their learning capabilities by applying nonlinear transformations to input data. This facilitates the extraction of intricate patterns from datasets. Commonly employed activation functions include Rectified Linear Unit (ReLU), Hyperbolic Tangent, Sigmoid, Softmax, Leaky ReLU, and Exponential Linear Unit (ELU). The selection of an activation function depends on the specific task at hand within the realms of machine learning, artificial intelligence, and data science. #machinelearning #artificialintelligence #activationfunctions #datascience
The best thing that ever happened to Deep Neural Networks is Activation functions. This function applies a Non Linear transformation to the input data gearing it to learn very complex patterns from data.
Examples of mostly used Activation Functions:
✅Rectified Linear Unit
✅Hyperbolic Tangent
✅Sigmoid
✅ Softmax
✅Leaky ReLU
✅Exponential Linear Unit (ELU)
Based on your task you will end up choosing one or the other.
Could you repost this for everyone in your network?