Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...

This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

1 School of Electronics and Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou, China 2 Department of Mechanical and Electrical Engineering, Henan Vocational College of ...

Running Python scripts is one of the most common tasks in automation. However, managing dependencies across different systems can be challenging. That’s where Docker comes in. Docker lets you package ...

ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...

Abstract: With an emphasis on convolutional neural networks (CNNs), this research does a thorough analysis of the effectiveness and suitability of the TensorFlow and PyTorch frameworks for image ...