Coding & Development

KANTINSLOT is an online platform specializing in slot games, offering a wide selection of 'gacor' (high-paying) slots with high Return to Player (RTP) rates. The platform aims to provide an easy and accessible gaming experience, emphasizing frequent 'maxwin' opportunities for both new and experienced players. It features popular games from renowned providers like Pragmatic Play, PG Soft, and Habanero, including titles such as Gates of Olympus and Sweet Bonanza. KANTINSLOT supports various secure payment methods, including local banks, e-wallets, and pulsa, ensuring safe and fast transactions for deposits and withdrawals. The platform also offers promotions and customer support.

Serviceware ITFM Software provides a comprehensive platform for IT Financial Management, enabling organizations to run IT like a business. It unifies planning, costing, billing, and benchmarking, integrating with existing ERP, ITSM, BI tools, and Cloud Services. The software helps address challenges like fragmented systems, low visibility into service costs, reactive budgeting, and manual billing processes. Key capabilities include cost transparency and optimization, automated charging and billing, data-driven planning and forecasting, IT cost benchmarking, and vendor and contract management. It's designed to help CIOs and CFOs gain the visibility needed to strategically steer IT investments.

WindyFlo is a no-code AI pipeline engineering platform designed to help users build and deploy AI features for their websites or applications without requiring any coding knowledge. The platform simplifies AI development through a drag-and-drop interface, allowing users to create custom AI pipelines by connecting various node blocks. It supports the customization of AI models and facilitates faster deployment of AI applications. WindyFlo aims to make AI development accessible to both AI enthusiasts and beginners, offering options to build pipelines from scratch or customize pre-built ones from its Pipeline Hub. The tool also addresses common challenges of traditional AI development, such as complex setups, extensive coding, manual updates, and high infrastructure costs, by providing an all-in-one solution with automatic AI model updates and no additional computing resource costs.

facexlib is an open-source library designed to provide ready-to-use face-related functions, leveraging current state-of-the-art open-source methods. It primarily offers PyTorch reference codes for various face processing tasks, including detection, alignment, recognition, parsing, matting, headpose estimation, and tracking. While it provides a collection of these algorithms, users are directed to the original repositories for training or fine-tuning. The library simplifies the integration of advanced face processing techniques into existing projects, making it a valuable resource for developers and researchers working with facial data. It is released under the MIT license, with individual components referencing their original licenses.

shapiq is a Python package designed for machine learning explainability, specifically focusing on Shapley Interactions and Shapley Values. It provides tools for approximating any-order Shapley interactions, benchmarking game-theoretical algorithms, and explaining feature interactions within model predictions. The library extends the functionality of the well-known SHAP package, offering a more comprehensive view of machine learning models by quantifying synergy effects between features, data points, or weak learners. It supports various interaction indices like k-SII, SV, FBII, and FSII, and includes functionalities for visualizing feature interactions through network plots. shapiq is intended for Python 3.12 and above, and can be installed via uv or pip.

ml-design-docs offers a comprehensive template for creating design documents specifically tailored for machine learning systems. Based on a detailed post, this guideline helps users think critically about problem definition, solution design, and feedback integration. It covers essential sections such as overview, motivation, success metrics, requirements & constraints, methodology (including problem statement, data, techniques, experimentation, and human-in-the-loop), and implementation details (high-level design, infra, performance, security, data privacy, monitoring, cost, integration points, risks & uncertainties). The template is designed to be adaptable, allowing users to select and add sections to best meet their project's needs, ensuring thorough planning and clear communication.

Reference is an open-source project offering a comprehensive collection of quick reference cheat sheets specifically designed for developers. It covers a wide array of topics, including numerous programming languages like Python, JavaScript, Go, and C++, as well as essential toolkits such as ChatGPT, VSCode, and Emmet. Additionally, it provides cheat sheets for Linux commands and keyboard shortcuts for popular applications like Adobe Photoshop, Figma, and GitHub. The platform encourages community contributions, allowing users to share their own cheat sheets or improve existing ones, making it a dynamic and continuously evolving resource. The primary and maintained domain for accessing these up-to-date cheat sheets is cheatsheets.zip.

BlockLabs is a technology company dedicated to leveraging Web3 and advanced web technologies to create innovative solutions for B2B companies. Their core mission is to automate business processes and accelerate growth through cutting-edge development. While the live website content is concise, the company's commitment to Web3 and next-generation web technology suggests a focus on decentralized applications, blockchain solutions, and other emerging internet paradigms. They aim to provide the foundational technology that allows businesses to thrive in an evolving digital landscape.

fake-bpy-module is a collection of fake Blender Python API modules specifically designed to enable robust code completion in popular Integrated Development Environments (IDEs). This tool significantly assists developers working with Blender's Python API by offering accurate suggestions and documentation, streamlining the development of Blender add-ons and scripting tasks. It supports a wide range of Blender versions, from 2.78 up to the latest daily builds, and can be installed via pip, pre-generated modules, or by manual generation. The project emphasizes long-term support and provides resources for bug reporting, feature requests, and community discussions, making it an essential utility for Blender Python developers.

TensorFlowASR is an open-source toolkit for automatic speech recognition (ASR) built on TensorFlow 2. It provides implementations of various advanced ASR architectures, including DeepSpeech2, Jasper, RNN Transducer, ContextNet, and Conformer. A key feature is the ability to convert these models to TFLite, which significantly reduces memory and computation requirements, making them suitable for deployment on devices with limited resources. The framework supports multiple languages, including English and Vietnamese, and offers functionalities for feature extraction and augmentations. It's designed for developers and researchers looking to build, train, and deploy high-performance speech recognition systems.

cnn-facial-landmark offers training code for facial landmark detection based on deep convolutional neural networks. This open-source project, built with TensorFlow, enables users to train their own models using custom datasets. The repository includes detailed instructions for getting started, installing prerequisites, and training/evaluating models. It supports exporting models for PC/Cloud applications using TensorFlow's SavedModel format. A companion tutorial is available, covering background, dataset preprocessing, model architecture, training, and deployment, making it accessible for beginners. The project also points to more advanced repositories for features like multiple public dataset support, advanced model architectures, data augmentation, and model optimization.

ddpm-segmentation is an official implementation of the paper "Label-Efficient Semantic Segmentation with Diffusion Models" (ICLR'2022). This open-source project investigates representations learned by state-of-the-art Denoising Diffusion Probabilistic Models (DDPMs) and demonstrates their value for downstream vision tasks. The tool offers a simple semantic segmentation approach that leverages these representations, showing superior performance in few-shot operating points compared to other methods. It includes implementations for DDPM, DatasetDDPM, MAE, SwAV, and DatasetGAN, along with pretrained models and scripts for training interpreters and generating synthetic datasets. The project is built upon datasetGAN and guided-diffusion techniques, providing a robust framework for research and application in semantic segmentation.

Magnet.me is a comprehensive career network designed to help students and professionals find their perfect job, traineeship, or internship. The platform connects over 450,000 students and professionals with more than 6,000 employers, ranging from startups to multinationals. A key feature is its AI career coach, which assists users in discovering suitable job opportunities, practicing interview skills, and making informed career decisions. Users can create a profile, connect with top employers, receive job matches based on their preferences, and even be approached by recruiters. The platform lists over 30,000 vacancies across various industries and locations, making it a robust resource for career development.

Falcon Robotics is an impact-driven deep-tech company specializing in Enterprise AI and Edge Computing. Their flagship platform, REIM, transforms raw data into connected knowledge, enabling multiple forms of AI. This ranges from generating actionable insights to facilitating autonomous decisions and actions at scale. The company focuses on delivering real-time intelligence from the cloud to the edge, even in challenging environments. Falcon Robotics connects people, machines, and data in real-time to power Industry 4.0, accelerate digital transformation, and advance space innovation. They offer solutions in Robotics, Drones, Exoskeletons, AI/ML Based Solutions, Data Fusion, and Augmented/Virtual Reality Tools.

SuperPicky is an AI-powered photo culling tool specifically designed for bird photographers, aiming to streamline the often tedious process of selecting the best shots. It leverages advanced AI to provide smart ratings based on head sharpness and aesthetic quality (TOPIQ), alongside precise focus detection by analyzing RAW focus points. The tool intelligently groups burst sequences, identifies over 11,000 bird species, and detects bird-in-flight (BIF) poses and bird eye positions, writing this valuable metadata directly to EXIF and IPTC tags. With its integrated result browser, photographers can efficiently filter, review, and compare images in a user-friendly interface. SuperPicky is ideal for wildlife and bird photographers seeking to drastically reduce post-processing time, enhance their workflow, and ensure they select only the highest quality images from large shooting sessions. It also offers a command-line interface and Lightroom plugin for advanced users.

Crepe offers a robust implementation of character-level convolutional networks for text classification, built on Torch 7. This open-source project allows users to reproduce the experimental results from the "Character-level Convolutional Networks for Text Classification" article published in NIPS 2015. It includes data preprocessing scripts to convert CSV datasets into a Torch 7 binary format and a training program. The tool is designed for technical users and researchers, providing a foundation for advanced text classification tasks. While it requires a specific environment, including Torch 7 and potentially a powerful GPU, it serves as a valuable resource for understanding and applying character-level CNNs.

AI DIAL Core is an open-source project designed to provide a unified API for various chat completion and embedding models, assistants, and applications. Built on Java 21 and Eclipse Vert.x, it offers a robust and scalable solution for integrating diverse AI functionalities. The tool supports HTTP proxy functionality and provides comprehensive configuration options for static and dynamic settings, identity providers, toolsets, security, and storage. Developers can deploy DIAL Core on Kubernetes using Helm charts, making it suitable for complex enterprise environments. Its modular design allows for flexible integration and management of AI resources, ensuring a consistent interface across different AI services.

Supercharge is a digital product innovation partner specializing in building AI-enabled digital products. They offer comprehensive services including digital product strategy, software engineering, data solutions, managed services, and agentic AI and AI engineering. Supercharge works with businesses to create impactful digital solutions, focusing on speed and quality. They have experience across various industries such as energy, healthcare, finance, insurance, mobility, and public sector. The company is committed to sustainability, aiming to maximize the positive impact of digital products and is a carbon-neutral company supporting charitable causes.

Page Canary is an AI-powered website quality assurance bot designed to proactively identify issues on your website. It leverages AI to control a web browser, mimicking a real user's interaction to uncover problems. The tool offers over 10 custom web page audits, including checks for SSL certificate validity, link functionality, accessibility, security best practices, and spelling errors. By catching defects early, Page Canary helps prevent website downtime and ensures a smooth user experience. It's suitable for businesses looking to maintain high website quality and save developer hours on manual testing.

NeuroBlock is an AI laboratory dedicated to enhancing AI models through the use of high-quality datasets. The platform provides comprehensive enterprise AI consulting services, assisting businesses in integrating and optimizing AI solutions. A key offering includes local and private AI integrations, ensuring data privacy and tailored performance for specific organizational needs. Additionally, NeuroBlock features an OpenData platform, designed to facilitate AI model training by providing access to diverse and curated datasets. The company also develops lead generation tools, leveraging AI to identify and engage potential customers. NeuroBlock aims to deliver AI solutions that are efficient, secure, and customized to client requirements.

Beyond42 is an Immersive Experience Platform (IXP) designed to transform physical spaces like university campuses, cultural sites, and corporate headquarters into intelligent, interactive digital twins. This platform enables organizations to scale presence, engagement, and revenue by offering virtual experiences such as global recruitment for universities, interactive exhibitions for cultural sites, and immersive events for corporate offices. Beyond42 also provides an API, allowing integration of its immersive 3D environments into other products. The platform has demonstrated success in enhancing cultural and historical sites, boosting student engagement, and revolutionizing event efficiency and accessibility through its digital twin technology.

Griddo is a no-code digital experience platform specifically tailored for the education sector, particularly universities. It empowers marketing and communication teams to manage their entire web ecosystem from a single, intuitive interface, eliminating the need for IT dependency. The platform facilitates rapid website creation, content management, and digital marketing actions, including SEO and branding. Griddo supports multi-site management, multilingual content, and offers a flexible CMS for building high-performance websites. It integrates natively with SEO functionalities and external tools like Google Tag Manager and Google Analytics, ensuring agility, scalability, and editorial autonomy for educational institutions.

Federated is a collection of Google research projects dedicated to advancing Federated Learning and Federated Analytics. Federated learning enables the training of a shared global model across numerous participating clients while ensuring their training data remains local. Federated analytics, on the other hand, focuses on applying data science methods to analyze raw data stored directly on users’ devices. Many projects within this repository leverage TensorFlow Federated (TFF), an open-source framework designed for machine learning and other computations on decentralized data. The repository serves primarily for reproducing experimental results from related papers, with each project intended as an independent unit rather than a reusable framework.

Falcon-H1-Tiny offers a series of compact language models designed to push the boundaries of AI capabilities at a small scale. These models are available on Hugging Face Spaces and are ideal for research and experimentation. Users can input prompts and receive generated responses from these lightweight but capable AI models, making them suitable for various applications including research paper analysis, data visualization, and the development of small-scale AI applications. The focus on models with 100 million parameters or less makes them particularly efficient and accessible for developers and researchers working with limited resources.