Search Results for "data mining project with code"

CodeGuide is a curated collection of Java development resources built from years of real-world engineering experience by the author, who has worked extensively in large-scale internet companies. The project serves as a structured and comprehensive learning path for developers who want to strengthen their understanding of Java fundamentals and core programming practices. It includes detailed explanations of design patterns, source code analysis, frameworks, algorithms, and real-world project...

certificate-transparency-go is a Go codebase for building and interacting with Certificate Transparency (CT) systems, from low-level parsing to full log operation. It includes forked ASN.1 and X.509 packages tailored to accept and analyze real-world certificates, including pre-certificates that stricter libraries would reject, supporting CT’s role as an ecosystem observatory. A TLS parsing library, CT data types, and multiple client libraries enable access to CT logs over HTTP and DNS, along...

multiOTP is a PHP class, a powerful command line utility and a web interface developed by SysCo systèmes de communication sa in order to provide a completely free and easy operating system independent server side implementation for strong two factors authentication solution. multiOTP supports hardware and software tokens with different One-Time Password algorithms like OATH/HOTP, OATH/TOTP and mOTP (Mobile-OTP). QRcode generation is also embedded in order to support provisioning of Google...

cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data.

...The models have achieved state-of-the-art results on benchmark datasets such as UCF101 and HMDB51, and also won first place in the CVPR 2017 Charades Challenge. The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs.