Computer Science and Programming

HTTP status codes are three-digit numbers that are returned by a web server in response to a client's request made to the server via HTTP (Hypertext Transfer Protocol). These status codes provide information about the outcome of the request, indicating whether it was successful, encountered an error, or needs further action. They are an essential part of the HTTP protocol, helping both clients (e.g., web browsers) and servers communicate effectively.

🔵 REST vs 🟣 GraphQL 🔵 REST: 👉 Stands for Representational State Transfer 👉 Well-established and widely adopted 👉 Uses predefined endpoints for data retrieval 👉 Great for simple, stateless operations 🟣 GraphQL: 👉 A modern query language for APIs 👉 Allows clients to request exactly what they need 👉 Reduces over-fetching and under-fetching of data 👉 Empowers front-end developers with data control Which one is right for your project? 🤔 Use 🔵 REST if: Simplicity and Convention: REST is straightforward and relies on a set of conventions. If you have a simple API with well-defined endpoints and actions, REST might be a good choice. Caching: RESTful APIs are typically easier to cache because the URLs for resources remain consistent. This can lead to better performance in scenarios where caching is crucial. Existing Ecosystem: If you're working with legacy systems or integrating with third-party APIs that follow REST principles, it may make sense to stick with REST for consistency. Use 🟣 GraphQL if: Flexibility: GraphQL allows clients to request exactly the data they need, which can lead to reduced over-fetching and under-fetching of data. This flexibility is especially beneficial for complex applications with varying data requirements. Efficiency: With GraphQL, you can often make a single request to fetch related data, reducing the number of API calls required compared to REST, which might require multiple requests to different endpoints. Real-time Data: If you need real-time updates and subscriptions, GraphQL's ability to provide live data can be a significant advantage. Team Expertise: If your development team is comfortable with GraphQL and prefers its query language, it might lead to faster development and easier maintenance.

Prod Software Release 1. Planning: - Identify the goals and features for the upcoming release. - Prioritize tasks based on importance and dependencies. - Define timelines and allocate resources accordingly. 2. Development: - Programmers start coding based on the planned features. - Regular code reviews and collaboration to maintain code quality. - Version control systems track changes for better collaboration. 3. Building Artifact: - Compile the source code into executable or deployable artifacts. - Generate documentation and other necessary files. - Automation tools can be used to streamline this process. 4. Testing: - Conduct various levels of testing (unit, integration, system, etc.). - Identify and fix bugs or issues. - Ensure compatibility with different platforms and configurations. 5. Release: - Once testing is successful, prepare for the release. - Generate release notes documenting changes and updates. - Coordinate with other teams for a smooth rollout. Environments: - Set up different environments for development, testing, and production. - Ensure consistency across environments to minimize deployment issues. - Monitor and troubleshoot any discrepancies between environments.

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Is AI making a real impact in the way you work or is it all hype? Stack Overflow recaps some of the top insights from their 2023 Developer Survey.💡 Explore what developers are thinking about the benefits, accuracy, and use cases for GenAI here.

Angular 17 and the new angular.dev site has been officially released. Here's a summary of what's new.

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Top 12 Tips for API Security: - Use HTTPS - Use OAuth2 - Use WebAuthn - Use Leveled API Keys - Authorization - Rate Limiting - API Versioning - Whitelisting - Check OWASP API Security Risks - Use API Gateway - Error Handling - Input Validation

Docker Architecture and Components 1. Docker Daemon (dockerd): - 𝗥𝗼𝗹𝗲: Manages Docker containers on a system. - 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: Building, running, and managing containers. 2. Docker Client (docker): - 𝗥𝗼𝗹𝗲: Interface through which users interact with Docker. - 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀: build, pull, run, etc. 3. Docker Images: - 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻: Read-only templates used to create containers. - 𝗥𝗼𝗹𝗲: Serve as the basis for creating containers. - 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆/𝗛𝘂𝗯: A storage and distribution system for Docker images. 4. Docker Containers: - 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻: Runnable instances of Docker images. - 𝗥𝗼𝗹𝗲: Encapsulate the application and its environment. 5. Docker Registry: - 𝗥𝗼𝗹𝗲: Store Docker images. - 𝗣𝘂𝗯𝗹𝗶𝗰 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆: Docker Hub. - 𝗣𝗿𝗶𝘃𝗮𝘁𝗲 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆: Can be hosted by users.

What is Kafka? Kafka is an open-source, distributed event streaming platform that serves as the central nervous system for data in modern enterprises. It's designed to handle real-time data feeds, process them efficiently, and make them available for a variety of applications in real-time. 🛠 Use Cases: - Real-time Analytics - Log Aggregation - Event Sourcing - Data Integration - Machine Learning Pipelines

Wondering how C++, Java, Python Work? 🔵 C++ C++ is like the superhero of programming languages. It's a compiled language, meaning your code is transformed into machine code that your computer can understand before it runs. This compilation process is crucial for efficiency and performance. C++ gives you precise control over memory and hardware, making it a top choice for systems programming and game development. It's like wielding a finely-tuned instrument in the world of code! 🎸💻 🔴 Java Java, on the other hand, is the coffee of programming languages. It's a compiled language too but with a twist. Java code is compiled into bytecode, which runs on the Java Virtual Machine (JVM). This bytecode can run on any platform with a compatible JVM, making Java highly portable and platform-independent. It's a bit like sending your code to a virtual coffee machine that serves it up just the way you like it on any OS! ☕️💼 🐍 Python Python is the friendly neighborhood programming language. It's an interpreted language, which means there's no compilation step. Python code is executed line by line by the Python interpreter. This simplicity makes it great for beginners and rapid development. Python's extensive library ecosystem and easy syntax make it feel like you're scripting magic spells in a magical world! 🪄🐍 In the end, the choice of programming language depends on your project's needs and your personal preferences. Each language has its strengths and weaknesses, but they all share the goal of bringing your ideas to life through code. 🚀💡 So, whether you're crafting the perfect C++ masterpiece, brewing up Java applications, or scripting Python magic, remember that programming languages are the tools that empower us to create amazing things in the digital realm. Embrace the language that speaks to you and keep coding! 💻🌟

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𝗛𝗼𝘄 𝘁𝗼 𝘁𝗲𝘀𝘁 𝘆𝗼𝘂𝗿 𝗔𝗣𝗜𝘀 𝗱𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝗳𝗿𝗼𝗺 𝗩𝗶𝘀𝘂𝗮𝗹 𝗦𝘁𝘂𝗱𝗶𝗼 𝗖𝗼𝗱𝗲? You can immediately do this from your Visual Studio Code, as Postman just released a VS Code extension that integrates API building and testing into your code editor. What you can do with the extension: 🔹𝗦𝗲𝗻𝗱 (𝗺𝘂𝗹𝘁𝗶𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹) 𝗿𝗲𝗾𝘂𝗲𝘀𝘁𝘀 🔹𝗦𝗲𝗻𝗱 𝗿𝗲𝗾𝘂𝗲𝘀𝘁𝘀 𝗳𝗿𝗼𝗺 𝘆𝗼𝘂𝗿 𝗵𝗶𝘀𝘁𝗼𝗿𝘆 🔹𝗨𝘀𝗲 𝗰𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀 🔹𝗨𝘀𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀 🔹𝗩𝗶𝗲𝘄 𝗮𝗻𝗱 𝗲𝗱𝗶𝘁 𝗰𝗼𝗼𝗸𝗶𝗲𝘀 ➡️Check it here

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80+ Jupyter Notebook tutorials on image classification, object detection and image segmentation in various domains 📌 Agriculture and Food 📌 Medical and Healthcare 📌 Satellite 📌 Security and Surveillance 📌 ADAS and Self Driving Cars 📌 Retail and E-Commerce 📌 Wildlife Classification library https://github.com/Tessellate-Imaging/monk_v1 Notebooks - https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/4_image_classification_zoo Detection and Segmentation Library https://github.com/Tessellate-Imaging/ Monk_Object_Detection Notebooks: https://github.com/Tessellate-Imaging/Monk_Object_Detection/tree/master/application_model_zoo

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🔭 GRES: Generalized Referring Expression Segmentation New benchmark (GRES), which extends the classic RES to allow expressions to refer to an arbitrary number of target objects. 🖥 Github: https://github.com/henghuiding/ReLA ⏩ Paper: https://arxiv.org/abs/2306.00968 🔎 Project: https://henghuiding.github.io/GRES/ 📌 New dataset: https://github.com/henghuiding/gRefCOCO 👉 @computer_science_and_programming

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Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold Paper: https://arxiv.org/abs/2305.10973 Github: https://github.com/XingangPan/DragGAN Project page: https://vcai.mpi-inf.mpg.de/projects/DragGAN/ 👉 @computer_science_and_programming

Test of Time: Instilling Video-Language Models with a Sense of Time GPT-5 will likely have video abilities, but will it have a sense of time? Here is answer to this question in #CVPR2023 paper by student of University of Amsterdam to learn how to instil time into video-language foundation models. Paper: https://arxiv.org/abs/2301.02074 Code: https://github.com/bpiyush/TestOfTime Project Page: https://bpiyush.github.io/testoftime-website/ 👉 @computer_science_and_programming

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ViperGPT: Visual Inference via Python Execution for Reasoning ViperGPT, a framework that leverages code-generation models to compose vision-and-language models into subroutines to produce a result for any query. Github: https://github.com/cvlab-columbia/viper Paper: https://arxiv.org/pdf/2303.08128.pdf Project: https://paperswithcode.com/dataset/beat 👉@computer_science_and_programming

Multivariate Probabilistic Time Series Forecasting with Informer Efficient transformer-based model for LSTF. Method introduces a Probabilistic Attention mechanism to select the “active” queries rather than the “lazy” queries and provides a sparse Transformer thus mitigating the quadratic compute and memory requirements of vanilla attention. 🤗Hugging face: https://huggingface.co/blog/informer ⏩ Paper: https://huggingface.co/docs/transformers/main/en/model_doc/informer ⭐️ Colab: https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multivariate_informer.ipynb 💨 Dataset: https://huggingface.co/docs/datasets/v2.7.0/en/package_reference/main_classes#datasets.Dataset.set_transform 👉@computer_science_and_programming

Efficient Teacher: Semi-Supervised Object Detection for YOLOv5 ✅ Efficient Teacher introduces semi-supervised object detection into practical applications, enabling users to obtain a strong generalization capability with only a small amount of labeled data and large amount of unlabeled data. ✅ Efficient Teacher provides category and custom uniform sampling, which can quickly improve the network performance in actual business scenarios. Paper: https://arxiv.org/abs/2302.07577 Github: https://github.com/AlibabaResearch/efficientteacher 👉@computer_science_and_programming

3D-aware Conditional Image Synthesis (pix2pix3D) Pix2pix3D synthesizes 3D objects (neural fields) given a 2D label map, such as a segmentation or edge map Github: https://github.com/dunbar12138/pix2pix3D Paper: https://arxiv.org/abs/2302.08509 Project: https://www.cs.cmu.edu/~pix2pix3D/ Datasets: CelebAMask , AFHQ-Cat-Seg , Shapenet-Car-Edge 👉@computer_science_and_programming

YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection SPATIO-temporal action detection (STAD) aims to detect action instances in the current frame, which it has been widely applied, such as video surveillance and somatosensory game. Paper: https://arxiv.org/pdf/2302.06848.pdf Github: https://github.com/yjh0410/YOWOv2 Dataset: https://drive.google.com/file/d/1Dwh90pRi7uGkH5qLRjQIFiEmMJrAog5J/view?usp=sharing 👉@computer_science_and_programming

Gen-1: The Next Step Forward for Generative AI Use words and images to generate new videos out of existing Introducing Gen-1: a new AI model that uses language and images to generate new videos out of existing ones. https://research.runwayml.com/gen1 ⭐️ Project: https://research.runwayml.com/gen1 ✅ Paper: https://arxiv.org/abs/2302.03011 📌Request form: https://docs.google.com/forms/d/e/1FAIpQLSfU0O_i1dym30hEI33teAvCRQ1i8UrGgXd4BPrvBWaOnDgs9g/viewform 👉@computer_science_and_programming

Audio AI Timeline Here we will keep track of the latest AI models for audio generation, starting in 2023! ▪️SingSong: Generating musical accompaniments from singing - Paper ▪️AudioLDM: Text-to-Audio Generation with Latent Diffusion Models - Paper - Code ▪️Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion - Paper - Code ▪️Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models - Paper ▪️Noise2Music ▪️RAVE2 - Paper - Code ▪️MusicLM: Generating Music From Text - Paper ▪️Msanii: High Fidelity Music Synthesis on a Shoestring Budget - Paper - Code - HuggingFace ▪️ArchiSound: Audio Generation with Diffusion - Paper - Code ▪️VALL-E: Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers - Paper 👉@computer_science_and_programming

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🔗 Link:- https://apitester.org A fully free mobile API client for interacting with APIs straight from your phone. Doesn't it sound fantastic? API Tester allows you to connect to whatever type of API you're working with, including REST, gRPC, SOAP, and GraphQL. Constructing HTTP requests with parameters, auth details, and body data requires only a few steps with a simple and optimized UI. You can also create WebSocket connections, import collections, and use global variables. API Tester was developed by a team of enthusiasts who feel that powerful apps simplifying work is the key to progress. The app is constantly updated to ensure that you have all of the top-tier features. Try it out for yourself, rate and review on the App Store and Google Play.

Cut and Learn for Unsupervised Object Detection and Instance Segmentation Cut-and-LEaRn (CutLER) is a simple approach for training object detection and instance segmentation models without human annotations. It outperforms previous SOTA by 2.7 times for AP50 and 2.6 times for AR on 11 benchmarks. Paper: https://arxiv.org/pdf/2301.11320.pdf Github: https://github.com/facebookresearch/CutLER Demo: https://colab.research.google.com/drive/1NgEyFHvOfuA2MZZnfNPWg1w5gSr3HOBb?usp=sharing 👉@computer_science_and_programming