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 ...
InfoWorld

Java or Python for building agents?

The surest way to value with AI is to use the tools that leverage your organization’s hard-won expertise and that integrate ...
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

“Pre-Train, Prompt” Framework to Boost Graph Neural Networks Performance in EEG Analysis

Abstract: Electroencephalography (EEG) is a vital non-invasive technique used in neuroscience research and clinical diagnosis. However, EEG data have a complex non-Euclidean structure and are often ...