Coding & Development

qikqiak.com is a comprehensive blog dedicated to exploring various cutting-edge technologies. It offers in-depth articles and resources on topics such as ChatGPT, containerization, Kubernetes, DevOps practices, Python, and Golang. The platform also delves into microservices architecture and other related technical subjects, providing valuable insights for developers and technology enthusiasts. The blog aims to keep its audience informed about the latest trends and best practices in the tech world, making complex concepts accessible through detailed explanations and practical examples. It serves as a knowledge hub for those looking to deepen their understanding and skills in these rapidly evolving domains.

recurrentjs is a Javascript library designed for implementing Deep Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) networks. Beyond these specific neural network types, the library offers general functionality to construct arbitrary expression graphs, over which it can perform automatic differentiation, similar to capabilities found in Python's Theano or Torch. This allows developers to build various neural networks and execute automatic backpropagation. The library provides core components like a Graph structure for managing matrix connections and a Mat class for 2-dimensional matrices, including their values and derivatives. It's an open-source tool, making it accessible for those looking to explore or implement neural networks in Javascript.

LongVideoBench is an AI tool designed for evaluating and benchmarking long video models. It provides a platform to view and sort leaderboard data based on different criteria, including accuracy by duration groups and question categories. This allows researchers and developers to compare the performance of various AI models in understanding and analyzing long-form video content. The tool is particularly useful for those working on video analysis and understanding, offering a structured way to assess model capabilities and identify areas for improvement. Hosted on Hugging Face Spaces, it leverages a robust infrastructure for data display and sorting.

Hexowatch is an AI-powered website monitoring and archiving tool designed to keep users informed about any changes on web pages. It offers 13 distinct monitoring types, including visual, content, price, source code, technology, availability, and WHOIS changes. Users can track specific HTML elements, keywords, sitemaps, API endpoints, backlinks, and RSS feeds. The platform is trusted by over 150,000 businesses and helps users stay ahead of competitors, track market prices, monitor product availability, and receive alerts for recruitment opportunities or property deals. Hexowatch also provides cloud archiving for legal and compliance purposes, ensuring a snapshot of every page change is accessible. It's a comprehensive solution for businesses and individuals needing to monitor web content without manual effort.

Xoilac TV is a leading online football streaming platform in Vietnam, offering live broadcasts of World Cup 2026 matches in high definition. The platform, also known as XoilacZ, provides comprehensive football information including match schedules, league standings, and real-time results, ensuring fans stay updated. It aims to be the top destination for live football streaming, investing significantly to deliver high-quality viewing experiences. Users can access a wealth of football-related content and enjoy matches with Vietnamese commentary, fostering a large community of fans.

AppPlatform is a cutting-edge, open-source AI application engineering platform designed to streamline the development process for large model training and inference applications. It achieves this through integrated declarative programming and low-code configuration tools, offering a powerful and scalable environment for software engineers and product managers. The platform supports the entire AI application development lifecycle, from concept to deployment. Its core architecture includes a backend based on the FIT framework for application management and functional extensions, and a React-based frontend with a visual interface for AI application development, an application marketplace, smart forms, and plugin management. Key features include a low-code graphical interface for intuitive AI app creation, a robust operator and scheduling platform supporting multiple programming languages, and a shared template store for collaboration and reuse of AI applications as functions, RAGs, or agents.

arkTS is an open-source VSCode plugin designed to enhance the development experience for HarmonyOS ArkTS applications. It offers a comprehensive suite of features including syntax highlighting, code completion, navigation, and diagnostics for the ArkTS language. The plugin integrates a fast ArkTS formatter, based on a Rust-written toolchain, and provides an emulator image manager consistent with DevEco Studio for creating, deleting, and managing devices and images. Developers can also manage OpenHarmony SDK installations, with automatic API version detection and prompts for download or switching. It includes rich snippets, perfect `$r` function completion, module.json5 support, and a Hvigor resource explorer panel. Additionally, arkTS offers an integrated file icon theme and extensive JSON Schema support for various configuration files.

Newera.ai specializes in developing and deploying custom AI systems for government and enterprise teams, helping them move from proof-of-concept to production rapidly. The platform focuses on execution over experimentation, delivering Minimum Viable Products (MVPs) within 1-4 weeks. Newera.ai trains AI solutions on client-specific data and context, ensuring relevance and performance in unique operational environments. All deployments are secured in private, isolated environments, adhering to enterprise-grade security and data ownership requirements. The systems are built to process both Arabic and English natively, adapting to mixed-language content and domain-specific terminology, making them suitable for diverse organizational workflows in operations, policy, and customer engagement.

Chinese-number-gestures-recognition is an open-source Android application designed to recognize Chinese number gestures from 0 to 10 using a convolutional neural network (CNN). The project includes both the Android app code for real-time gesture recognition via a mobile camera and PC-side code for data processing and model training. It supports development environments like Python 3.6 with TensorFlow-gpu and Android Studio with TensorFlow Lite and OpenCV. The project also provides datasets, including raw images, data-augmented images, and compressed H5 datasets, along with pre-trained models. While the PC-trained models show high accuracy, the app's real-world performance can vary in complex environments.

SvgTrace transforms raster images like JPG and PNG into scalable vector graphics (SVG) with unlimited colors. The tool leverages AI for enhanced upscaling, converting low-resolution images into high-quality SVG files effortlessly. It specializes in creating color-layered SVG files, which are ideal for multi-layer SVGs, cut files, 3D layers, plywood cutting, paper cutting, and 3D mandala projects. SvgTrace also provides a powerful manual editor, allowing users to adjust and modify each layer with options like cutting, erasing, and copying. It caters to both individuals with a free web-based converter and professionals with Pro plans and an email conversion service for production workflows.

DeepLearningTutorials is a valuable resource for anyone looking to delve into the field of deep learning. It provides detailed tutorial notes and corresponding Python code, specifically designed to introduce users to some of the most important deep learning algorithms. The tutorials emphasize learning multiple levels of representation and abstraction, crucial for processing data like images, sound, and text. A key feature is its integration with Theano, a Python library that simplifies deep learning model development and offers the capability to train models efficiently on a GPU. The project is hosted on GitHub, ensuring accessibility to its code and documentation, and encourages users to browse the tutorials online for an optimal learning experience.

deep-learning-from-scratch-4 is an open-source GitHub repository that serves as the support site for the book "Deep Learning from Scratch 4: Reinforcement Learning Edition" (O'Reilly Japan, 2022). It provides all the source code used in the book, organized by chapter, along with common utility code. The repository also offers Jupyter Notebook versions of the code, which can be run directly on cloud services like Google Colab, Kaggle Notebook, and Studio Lab for interactive learning. It supports Python 3.x and requires libraries such as NumPy, Matplotlib, OpenAI Gym, and DeZero (or PyTorch). The project is licensed under the MIT License, allowing for free commercial and non-commercial use, making it an excellent resource for students and developers exploring reinforcement learning.

deep-fonts is an open-source project available on GitHub that leverages deep learning to generate unique fonts. This tool provides a platform for users to explore and create new typefaces, offering a novel approach to font design. It includes scripts for creating datasets, training models, and generating fonts, making it a comprehensive solution for those interested in the intersection of AI and typography. The project also features examples of generated fonts and visualizations, demonstrating its capabilities in producing diverse and experimental typographic styles. It's ideal for researchers, developers, and designers looking to experiment with AI-driven font creation.

Document-cn-translation-of-skywalking was a community-driven GitHub repository offering a Chinese translation of the Apache SkyWalking documentation. This resource aimed to make the technical documentation more accessible to Chinese-speaking users. However, the project has been archived and is no longer updated, with a clear directive for users to refer to the official Apache SkyWalking website for the most current AI-powered documentation. While it served as a valuable translation effort, its content is now considered outdated, and users seeking up-to-date information should consult the official source.

imbalanced-learn is an open-source Python package designed to address the common challenge of imbalanced datasets in machine learning. It offers a variety of re-sampling techniques to balance the class distribution, which is crucial for optimizing the performance of most classification algorithms. The package is fully compatible with scikit-learn, making it a seamless addition to existing machine learning workflows. It supports essential dependencies like NumPy, SciPy, and scikit-learn, with optional support for Pandas, TensorFlow, and Keras for broader data handling and model integration. The tool is part of the scikit-learn-contrib projects and provides comprehensive documentation, installation guides, and examples to help users effectively implement its functionalities.

GraphSAINT is an open-source framework designed for efficient and accurate training of Graph Neural Networks (GNNs) on large-scale graphs. It introduces a novel minibatch method that samples small subgraphs from the full training graph, allowing for complete GNN construction and propagation on these subgraphs without further layer sampling. This approach addresses the 'neighbor explosion' problem common in other methods, leading to linear computation cost with GNN depth and improved scalability. GraphSAINT supports various GNN architectures like GraphSAGE, GAT, JK-Net, GaAN, and MixHop, and offers multiple graph samplers including Node, Edge, RW, MRW, and Full graph. It provides implementations in both TensorFlow and PyTorch, making it flexible for researchers and developers working with deep GNNs.

Gemini Business2API functions as an OpenAI-compatible API gateway, enabling users to leverage Gemini Business capabilities through a familiar interface. This tool is designed with multi-account load balancing, ensuring efficient distribution of requests across multiple Gemini Business accounts. It supports advanced multimodal features, including image and video generation, as well as comprehensive file parsing. The platform includes a built-in management panel for streamlined administration, allowing for unified management of account pools, system settings, and operational status. Key features like account import/export, batch operations, and status filtering enhance usability. It also offers flexible deployment options via Docker Compose or an interactive installation script, making it accessible for various technical setups.

The LangChain-Chinese-Getting-Started-Guide is an open-source tutorial designed to help Chinese speakers learn and utilize the powerful LangChain framework. It covers essential concepts such as LLM invocation, prompt management, document loaders, text splitters, vector stores, chains, and agents. The guide provides practical examples, including performing Q&A with OpenAI models, integrating with Serpapi for internet searches, and summarizing long texts. It also addresses common challenges like API token limits and offers solutions using LangChain's features. The tutorial is actively maintained on GitHub, with updates and code examples available for hands-on learning.

Machine-learning-engineering-for-production-public serves as the official public repository for DeepLearning.AI's Machine Learning Engineering for Production Specialization. This resource is designed to support students and professionals in understanding the intricacies of deploying machine learning models into real-world production environments. The repository contains various materials, including course content, labs, and other public resources relevant to the specialization's curriculum. While it provides valuable learning assets, the repository is currently not accepting pull requests for contributions. It is an essential companion for anyone undertaking the DeepLearning.AI MLEP Specialization, offering practical insights and foundational knowledge for machine learning engineering.

Paddle3D is an open-source, end-to-end deep learning 3D perception toolkit developed by PaddlePaddle. It provides a flexible framework for handling various 3D data formats and supports integration with PaddleDetection and PaddleSeg for 2D vision capabilities. The toolkit features a rich model library covering mainstream 3D perception algorithms across monocular, point cloud, and multi-camera modalities, including detection and segmentation tasks. It offers full-process support from data processing and model building to training, optimization, and deployment, with compatibility for major 3D datasets like KITTI, nuScenes, and Waymo. Paddle3D is optimized for performance on various autonomous driving chips and seamlessly integrates with the Apollo autonomous driving platform.

named_entity_recognition is an open-source project dedicated to Chinese named entity recognition (NER), offering practical implementations of several prominent models. It includes Hidden Markov Model (HMM), Conditional Random Field (CRF), Bi-directional Long Short-Term Memory (BiLSTM), and a hybrid BiLSTM+CRF model. The project utilizes a resume dataset for training and evaluation, providing detailed accuracy, recall, and F1 scores for each model. It serves as a valuable resource for researchers and developers interested in NLP, particularly in the context of Chinese NER, allowing for direct comparison and understanding of different algorithmic approaches.

Reinforcement-Learning-in-Robotics is a comprehensive, open-source learning repository dedicated to reinforcement learning techniques specifically applied in the field of robotics. It serves as a private learning resource, offering insights into various aspects of AI in robotics, including reasoning and representation learning for developing real intelligence. The repository features detailed content on foundational reinforcement learning concepts, model-based RL, probabilistic methods in robotics, structured probabilistic models, and efficient RL techniques. It also delves into meta-learning, imitation learning, and multi-agent reinforcement learning, providing a valuable resource for developers and researchers interested in the intersection of AI and robotics.

Tesollo is a robotics company that designs and manufactures advanced robotic grippers and automation solutions. Their core offerings include the Delto Gripper series, which features multi-joint robotic hands optimized for handling diverse objects, including irregularly shaped items. Tesollo also provides comprehensive robotic automation systems, such as picking solutions (DS-PICK) and palletizing solutions (DS-PAL), aimed at improving efficiency and value in industrial settings. The company emphasizes innovative technology to solve complex customer problems and drive human-centered innovation and sustainable growth in the robotics sector. Tesollo's products are designed for durability and maintainability, with modular designs like the DG-3F gripper.

PyHealth is a comprehensive, open-source deep learning Python toolkit designed to support clinical predictive modeling for both ML researchers and medical practitioners. It aims to make healthcare AI applications easier to develop, test, and deploy, offering flexibility and customizability. Key features include a modular 5-stage pipeline, a healthcare-first approach with support for medical codes and clinical datasets like MIMIC and eICU, and over 33 pre-built models with production-ready trainers and metrics. The toolkit supports more than 10 healthcare tasks and datasets, providing fast data processing for quick experimentation. PyHealth also includes independent modules for medical code mapping (pyhealth.medcode) and medical code tokenization (pyhealth.tokenizer), enhancing its utility for complex healthcare data.