Deep Learning with Yacine on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, ...
Deep Learning with Yacine on MSN

RMSProp Optimization from Scratch in Python

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...
InfoWorld

7 newer data science tools you should be using with Python

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...
Frontiers

Spiking Neural Networks at Scale: Learning Algorithms, Architectures, and Real-World Applications

Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...
Analytics Insight

NumPy vs. PyTorch: What’s Best for Your Numerical Computation Needs?

Overview: NumPy is ideal for data analysis, scientific computing, and basic ML tasks.PyTorch excels in deep learning, GPU ...
IEEE

Two-Stage Real-Time Carbon Emission Monitoring for Low-Carbon Power System Operation: A Graph Neural Network-Based Approach

Abstract: As carbon emissions reduction is becoming increasingly important for sustainable development and carbon neutrality targets, the concept of carbon emission market has been recently proposed ...
IEEE

Efficient Group Cosine Convolutional Neural Network for EEG-Based Seizure Identification

Abstract: Epilepsy is a common neurological disease, and its diagnosis usually depends on labor-intensive visual inspection of electroencephalogram (EEG). Although various deep learning-based seizure ...