This architecture was tested based on solving two problems. The first of these is the recognition of handwritten digits from the largest MNIST database. The recognition accuracy of the system ...

By focusing on specific workload types, organizations can also tailor caching strategies, improving cache hit rates from an average of 72.3% to 91.7%, leading to reduced database load and faster ...

This project demonstrates the implementation of a Convolutional Neural Network (CNN) from scratch using Python and NumPy ... The project also features a practical application on the MNIST dataset for ...

Python DB API client library for CrateDB, using HTTP.