Muhammad FaheemGenerative Configurations of Transformer-Based Language ModelsUnderstanding the Inference Configuration Parameters for Optimizing Transformer-Based Language Models.Nov 21
InAI AdvancesbyFrancesco FrancoThe Softmax Activation Function with KerasWhen you’re creating a neural network for classification, you’re likely trying to solve either a binary or a multiclass classification…Nov 134
heping_LUSigLIP vs. CLIP: The Sigmoid AdvantageEnhancing Quality and Efficiency in Language-Image Pre-TrainingSep 25Sep 25
InTowards Data SciencebyReza BagheriA Visual Understanding of the Softmax FunctionThe math and intuition behind the softmax function and its application in neural networks and softmax regressionNov 31Nov 31
MaribooIs Attention really off by one?While browsing my Twitter history (excuse me, my X history; although I maintain that Twitter turned X should surely be named TwiX), I…Jul 11Jul 11
Muhammad FaheemGenerative Configurations of Transformer-Based Language ModelsUnderstanding the Inference Configuration Parameters for Optimizing Transformer-Based Language Models.Nov 21
InAI AdvancesbyFrancesco FrancoThe Softmax Activation Function with KerasWhen you’re creating a neural network for classification, you’re likely trying to solve either a binary or a multiclass classification…Nov 134
heping_LUSigLIP vs. CLIP: The Sigmoid AdvantageEnhancing Quality and Efficiency in Language-Image Pre-TrainingSep 25
InTowards Data SciencebyReza BagheriA Visual Understanding of the Softmax FunctionThe math and intuition behind the softmax function and its application in neural networks and softmax regressionNov 31
MaribooIs Attention really off by one?While browsing my Twitter history (excuse me, my X history; although I maintain that Twitter turned X should surely be named TwiX), I…Jul 11
InAI-EnthusiastbyDeepankar SinghFrom Logits to Probabilities: Understanding Softmax in Neural NetworksDiscover how the Softmax function converts raw neural network outputs into clear probabilities, enabling confident multi-class predictions!Oct 30
Soumallya BishayeeThe Basic Concept of Autoencoder — The Self-supervised Deep LearningAutoencoder is a unsupervised deep learning network. It learns efficient data representation, which means encoding. It is unsupervised…Apr 13, 2023
mdPart VI: Improving the Image Classifier with CNN“Convolutional neural networks (CNNs or ConvNets) are used to perform a multitude of perception tasks for self-driving cars (SDCs)…Oct 3
