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Best Excel Add-Ins for Data Analysis in 2025

Excel add-ins are crucial for enhancing data analysis when Excel's built-in functionalities are insufficient.
Add-ins can simplify data cleanup, improve visualization, and aid in manual computation.
Choosing the right add-in is key for enhancing productivity and workflow integration.
Consider factors like automation, connectivity, pricing, and user reviews when selecting an add-in.
Top add-ins for 2025 include Power Query, Solver, XLSTAT, Ablebits, Charticulator, Kutools, and more.
Power Query excels in data cleaning, Solver in optimization, XLSTAT in statistical analysis, and Ablebits in data management.
Charticulator is great for custom chart creation, while Kutools focuses on time-saving utilities.
XLSTAT is suitable for beginners, Lucidchart Diagrams for diagram creation, and Atoti for real-time data handling.
Stock Connector is ideal for tracking live stock data, while off-the-shelf add-ins may not meet all specific needs.
For custom Excel add-ins, SCAND offers tailored solutions to optimize workflows and data analysis.

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Medium

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Rust-Powered Vector Databases: The Future of AI Search Is Here

Rust-based vector databases are gaining popularity for their speed, safety, and scalability.
Rust is emerging as the go-to language for developers, startups, and AI innovators.
Vector databases store high-dimensional representations of data for semantic search, recommendation engines, AI chatbots, and anomaly detection.
Rust delivers high performance and efficiency, making it ideal for compute-intensive and memory-intensive systems.

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Idownloadblog

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How to use Focus Stacking to increase depth of field in your photos

Focus Stacking is a technique used by photographers to combine multiple images with different focus points to create a single image with an extended depth of field.
This method can be applied with any camera, but dedicated camera bodies may yield better results, especially those supporting automatic Focus Bracketing.
Focus Stacking helps increase the depth of field without compromising light intake, unlike adjusting the aperture setting on a lens.
Certain cameras offer Focus Bracketing, a feature where multiple images with varying focus points are automatically captured for later Focus Stacking.
In macro, landscape, and product photography, Focus Stacking is commonly used to capture fine details and ensure the entire subject is in focus.
To perform Focus Bracketing, settings including focus order, step width, and shot amount need configuration based on the camera's capabilities.
The manual Focus Bracketing process involves setting up a tripod, adjusting manual focus, and capturing multiple images with different focal points.
Focus Stacking is then done using software like Adobe Photoshop or Helicon Focus to blend the focus points of the bracketed images into a single focused image.
Helicon Focus, a popular choice for Focus Stacking, allows you to import images, render focus stacking, and save the final blended image on your computer.
Overall, Focus Stacking and Focus Bracketing are powerful tools that can significantly enhance the outcome of your photography by expanding the depth of field and focus range.

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Engadget

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Roblox parental controls now include a block button

Roblox is updating its parental control features to give parents more visibility and control over their children's activities on the platform.
Parents can now view their child's friend list and block users on their behalf, as well as block specific experiences within Roblox.
Roblox will provide more detailed screen time metrics, allowing parents to see the top 20 experiences in which their child has spent the most time.
These updates aim to address concerns about child safety on the platform, in response to a broader reckoning about the impact of online platforms on teens.

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Alvinashcraft

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Dew Drop – April 2, 2025 (#4395)

The Dew Drop for April 2, 2025, #4395 highlighted various notable articles and links from the tech industry.
It covered topics including advancements in AI on Windows, contributions to the Uno Platform, new Azure AI Foundry innovations, and Docker Desktop 4.40 updates.
Web and cloud development articles discussed .NET on Heroku, Docker image layers, Blazor authentication, AWS vs. Azure, htmx usage for building dynamic apps, and more.
Articles related to WinUI, .NET MAUI, and XAML featured WinUI3Localizer for localizing apps, a guide on adding a WinForms rich text editor, and linear support vector regression using C#.
AI-focused topics covered Rook AI introduction, GitHub Copilot insights, OpenAI's GPT-4o improvements, and the integration of AI in healthcare with Model Context Protocol.
Design, methodology, and testing articles discussed MSIX flat bundle application packages, SNI updates for Azure DevOps, microservices with Spring Boot, and battling code duplication.
Additionally, there were links to various screencasts, podcasts, events, database updates, PowerShell commands, and miscellaneous tech news.

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Medium

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Earning Through Games:

Competitive gaming, also known as esports, is a lucrative industry where professional gamers earn through tournaments, sponsorships, and endorsements.
Streaming gameplay on platforms like Twitch or YouTube allows gamers to monetize through ads, subscriptions, and donations.
Game testers play unreleased games and earn by identifying bugs and issues for game development companies.
Creating and selling in-game items in virtual economies of popular games can be a profitable approach.

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Tech Radar

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Latest Meta AR smart glasses leak has killed my interest before they’re even official

Leaks reveal new details of Meta's upcoming smart glasses, codenamed Hypernova.
The glasses will feature a monocular design with a single display in the lower-right corner of the right lens.
They will offer similar features to the current Meta Ray-Ban smart glasses, including photo/video capture and WhatsApp notifications, as well as a new maps app for navigation.
Insiders predict the price of the smart glasses to be in the range of $1,300-$1,400.

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Medium

Ever since I was a kid, I’ve lovedtaking things apart—remote controls, toy cars, even my old laptop…

The author's passion for engineering began at a young age, building various DIY projects and experimenting with different materials.
Discovering the power of CAD and design software fueled the author's interest in engineering, realizing it was about more than just physical building.
The author chose mechanical engineering over other fields due to their interest in the physical mechanics of machines and hands-on design.
The author is currently focused on learning about AI-powered mechanical design and how machine learning can optimize engineering processes.

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Tech Radar

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Forget the Nintendo Switch 2 – I’m more excited that Microsoft could be making Windows 11 gaming handhelds even better with a new ‘handheld mode’

Recent clues in Windows 11 suggest a new 'full screen experience' for gaming handhelds, hinting at a potential 'handheld mode' with customizable layouts for users.
The speculation is based on changes spotted in a Windows 11 preview build related to a 'GamingPosture' category that includes references to a 'full screen experience' mode suited for small screens of gaming handhelds.
The current issue with Windows 11 on gaming handhelds is its clunky and challenging interface on small screens, prompting discussions of a 'handheld mode' to enhance usability.
Microsoft is seemingly taking steps to optimize Windows 11 for gaming handhelds, with past developments like a 'compact mode' for the Xbox app on PC and improvements to the Game Bar, indicating a push towards enhanced handheld support.
Rumors of a 'handheld mode' have long circulated, and recent changes in Windows 11 point towards a potential gaming portable-friendly interface, indicating Microsoft's focus on enhancing the OS for handheld devices.
Considering the leaked clues and recent improvements targeting handheld usability within Windows 11, there is growing speculation that Microsoft is committed to making the OS more suitable for gaming handhelds.
While the rumored Xbox handheld from Asus may be the first to leverage this new full-screen UI experience in Windows 11, it is essential to approach these potential developments with caution until further concrete details emerge.
The enhancements in Windows 11 suggest a dedicated effort by Microsoft to compete effectively in the handheld gaming space, potentially aligning with Valve's successful SteamOS interface featured in the Steam Deck.
Recent patches on Windows 11 and collaborations with partners like Asus indicate a strategic shift towards optimizing the OS for gaming handhelds, setting the stage for a more immersive and user-friendly experience.
As Microsoft gears up to potentially unveil a new 'handheld mode' for Windows 11, the focus on enhancing the interface for gaming handhelds signals a significant advancement in tailoring the OS for portable gaming experiences.
The evolving landscape of Windows 11 for handhelds highlights a notable shift in Microsoft's approach, paving the way for a more seamless and immersive gaming experience on portable devices.

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Dev

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How to create a decentralized AI agent with Gaianet.

Decentralized AI is gaining importance in the evolving AI ecosystem, offering solutions to centralized AI problems.
True decentralized AI agents feature infrastructure decentralization, model ownership, data sovereignty, resilience, reduced censorship risk, and knowledge diversity.
Gaianet is a decentralized computing infrastructure enabling the creation of personalized AI agents with unique characteristics.
It provides a web-based chatbot UI, an OpenAI-compatible API, and customization options for AI models and knowledge bases.
Gaianet democratizes AI creation by allowing individuals and businesses to deploy, scale, and monetize their AI agents independently.
The process of setting up a Gaianet node involves installation, initialization, and customization through model selection and knowledge base creation.
Users can integrate Gaianet nodes with various applications in the OpenAI ecosystem for enhanced functionality.
Benefits of creating decentralized AI agents include ownership, customization, privacy, monetization, and interoperability.
Gaianet allows users to monetize their AI agents through the Gaianet Protocol by setting pricing for API access.
Creating decentralized AI agents with Gaianet opens new possibilities for personalized AI experiences, catering to developers, businesses, and knowledge workers.

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Pcgamer

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OpenAI finalises deal for $40 billion in investments, raising company value up to $300 billion, but there's a catch to receive it all

OpenAI has secured $40 billion in investments, raising its company value up to $300 billion.
SoftBank Group leads the funding with an initial investment of $7.5 billion, along with $2.5 billion from an investment group that includes Microsoft.
If OpenAI remains non-profit by the end of 2025, the investment from SoftBank will decrease to $20 billion instead of the expected $30 billion.
The shift to for-profit raises questions about the company's original non-profit mission and potential implications for AI research and financial incentives.

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Dev

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Let Cursor Talk to Your APIs in Minutes! The Magic Bridge You Never Knew You Needed

The integration of Apidog MCP Server with Cursor revolutionizes the way developers work with APIs, eliminating the need for constant context-switching between coding and API documentation.
The common problem of debugging due to outdated API documentation is addressed by providing AI assistants like Cursor direct access to specific API blueprints through the MCP Server.
Setting up the Apidog MCP Server is straightforward, requiring minimal configuration steps, including obtaining an access token from Apidog and project ID identification.
By configuring Cursor with the obtained information, developers enable their AI assistants to generate code accurately aligned with the API specifications in a matter of minutes.
Examples demonstrate the capabilities of this integration, such as generating TypeScript interfaces, updating code with API changes, and creating complete API clients effortlessly.
Key benefits include faster API integration, reduced errors, synchronized documentation and code, and streamlined onboarding for new team members.
Pro tips suggest meaningful MCP server configurations, specific prompting techniques, and securing access tokens for enhanced usability.
The integration offers immediate and tangible benefits, enhancing developer productivity by saving time, minimizing errors, and making API work more enjoyable.
Implementing this integration is a valuable investment that improves efficiency, accuracy, and overall satisfaction in working with APIs, empowering developers to focus on coding rather than documentation.
Take advantage of this magic bridge between Apidog and Cursor to boost your development workflow and experience the seamless synergy of AI assistance with accurate API insights.
Embrace this tool to enhance your productivity, reduce errors, and unlock the full potential of your AI assistant in coding tasks involving API interactions.

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Webkul

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User Guide for WooCommerce WhatsApp Order Notifications

WooCommerce WhatsApp Order Notifications plugin enables automated order updates via WhatsApp.
Admin can send manual updates and notifications from the order editing page.
Seamless integration with WooCommerce ensures organized order details.
Enhances customer communication and provides fast updates via WhatsApp.

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Perficient

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Log Framework Integration in Azure Functions with Azure Cosmos DB

Logging is crucial for cloud application development, and Azure Functions lacks built-in logging to a centralized database.
Integrating NLog with Azure Functions enables logging into Cosmos DB, ensuring a unified logging approach.
Steps to integrate logging framework in Azure Functions:
Create an Azure Function project, Install necessary NuGet packages, Configure NLog, Create a log database, Define variables, Configure NLog in Startup.cs, Add logs in necessary places, Deploy the function.

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Medium

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How Machine Learning Works: A Simple Explanation for Beginners

Machine learning is about teaching computers to recognize patterns in data without explicitly programming them for every possible scenario.
The process starts with a dataset, which can be of different types and quality.
To teach the computer to recognize patterns, a machine learning algorithm is used. These algorithms fall into three main categories: supervised, unsupervised, and reinforcement learning.
Supervised learning involves training a model using labeled data with a known answer.

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