Analytics Insight

Top 10 Data Science Concepts You Must Learn in 2026

Key Takeaways -   To understand data science, one needs a lot of technical expertise along with business understanding. Generative AI, MLOps, and clou ...
GitHub

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

Here is an article about Using HDF5 with Python. Run the following commands to generate train/test/val dataset at data/{METR-LA,PEMS-BAY}/{train,val,test}.npz. As the ...
IEEE

Event-Based Spiking Neural Networks for Object Detection: A Review of Datasets, Architectures, Learning Rules, and Implementation

Abstract: Spiking Neural Networks (SNNs) represent a biologically inspired paradigm offering an energy-efficient alternative to conventional artificial neural networks (ANNs) for Computer Vision (CV) ...
GitHub

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

Here is an article about Using HDF5 with Python. Run the following commands to generate train/test/val dataset at data/{METR-LA,PEMS-BAY}/{train,val,test}.npz. As the ...
IEEE

Deep Learning Methodology for Charging Management Applications in Battery Cells Based on Neural Networks

Abstract: A Battery Energy Storage System (BESS) plays an important role in achieving energy transition and climate change mitigation, with charging management applications being a crucial topic to ...
Hackaday

Understanding Deep Learning: Free MIT Press EBook For Instructors And Students

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...
Hacker

Neural Network Layers: All You Need Is Inside Comprehensive Overview

This publication provides an in-depth overview of various neural network layers, including their historical development, mathematical formulations, and code implementations. We cover common layer ...
eLife

Remapping in a recurrent neural network model of navigation and context inference

This important work provides evidence that artificial recurrent neural networks can be used to investigate neural mechanisms underlying reversible remapping of spatial representations. Authors perform ...
Frontiers

Video frame prediction of microbial growth with a recurrent neural network

The recent explosion of interest and advances in machine learning technologies has opened the door to new analytical capabilities in microbiology. Using experimental data such as images or videos, ...
Frontiers

Forecasting the Amount of Traffic-Related Pollutant Emissions by Neural Networks

Continuous urbanization has led to a significant increase in traffic density in large cities and a concomitant growth of vehicle emissions (Davis et al., 2005; Perugu, 2019). An effective way to ...