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Remove Vowel-java,PasswordValidator,Regex,Password Valitation

Removed vowels from the given word, displaying the remaining characters.
Found vowels in the given word and displayed them.
Validated a password by checking if it contained uppercase, lowercase, numbers, and special characters.
Explained the regex pattern for validating a string starting with PR followed by exactly 6 digits.

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Bigdataanalyticsnews

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Transformer Models for Code Translation: Modernizing Legacy Applications with Gen AI

Legacy applications hinder business agility and require modernization for efficiency in today's market.
Legacy code poses security risks, scalability issues, and innovation challenges.
Transformer models for code translation offer solutions to modernize legacy systems.
Security risks in legacy systems stem from outdated languages and frameworks, making them vulnerable to cyberattacks.
Transformer models eliminate insecure dependencies, enforce encryption standards, and ensure compliance.
Scalability issues in legacy code can be addressed by translating into modern languages supporting cloud integration.
Innovation paralysis due to legacy maintenance can be overcome by automating code translation with transformers.
Transformer models are effective in context-aware translation, learning from large codebases, and handling complexity.
Transformers accelerate code translation, ensuring accuracy and adherence to modern standards in a scalable manner.
AI-powered modernization using transformers aids in speed, cost efficiency, and futureproofing systems.

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Medium

444

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Bug of the week #2

In C++, variables must be declared with a type to inform the compiler about the kind of data the variable will hold.
A declaration without a type leads to a syntax error in C++ compilation.
Adding a type in variable declaration resolves this issue.
Using 'auto' in variable declaration for type deduction requires initialization for the compiler to determine the type.

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Javacodegeeks

390

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Introduction to Apache Beam Using Java: A Beginner-Friendly Guide to Unified Data Processing

Apache Beam is an open-source, unified model for defining both batch and streaming data-parallel processing pipelines, allowing developers to write jobs that can run on various execution engines.
Apache Beam provides a high-level programming model with a unified API for batch and streaming, portability across multiple runners, and support for windowing, event time, triggers, and watermarks.
Java is the primary SDK for Apache Beam, offering mature API, better performance tuning options, wide usage in enterprise systems, and compatibility with Maven and Gradle for dependency management.
Apache Beam's unified API allows developers to define pipelines that can be configured for either batch or streaming at runtime, making it versatile for processing both bounded and unbounded datasets.

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Towards Data Science

427

Strength in Numbers: Ensembling Models with Bagging and Boosting

Ensembling in machine learning combines predictions from multiple models for creating powerful models, reducing variance, bias, and overfitting.
Bagging stabilizes ML models by reducing variance, creating an ensemble of models by bootstrapping the dataset, training models, and averaging or majority voting predictions.
Bagging works well for high-variance models like decision trees, improving model robustness to data fluctuations and spurious relationships.
A bagging example demonstrates how averaging predictions from multiple trees can reduce variance and improve model accuracy.
Boosting reduces bias by sequentially training models to correct predictions of previous models, enhancing predictions and model performance.
Boosting iteratively improves predictions by updating residual predictions or adding more weight to poor predictions, reducing bias and potentially variance.
Important parameters in boosting include the number of trees, tree depth, and learning rate, which affect model performance and overfitting.
Boosting uses a learning rate to discount residual predictions, mitigating overfitting and balancing the influence of individual trees in the ensemble.
Bagging and boosting have distinct characteristics: bagging focuses on reducing variance while boosting aims to reduce bias in weak learners.
In practice, bagging and boosting are usually implemented using advanced algorithms that enhance the basic concepts for improved model performance.
Ensembling techniques like bagging and boosting are valuable tools for data scientists to enhance model accuracy and generalization across various machine learning applications.

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PlanetPython

363

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Django Weblog: DjangoCon Europe and beyond

DjangoCon Europe 2025 was a successful event, celebrating Django's 20th birthday and emphasizing the importance of community involvement and sustainability of the project.
Challenges highlighted included the need for more code reviews and fundraising support to ensure the growth of the Django Software Foundation.
Discussions during the conference focused on diversity, equity, inclusion, membership management, and website content improvement, aiming for transparency and future contributions.
Upcoming events include PyCon US 2025, PyCon Italia 2025, EuroPython 2025, DjangoCon Africa 2025, and DjangoCon US 2025, all with plans to continue celebrating Django's 20th birthday.

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Dev

1.4k

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How to Insert a Div with JavaScript in Madcap Flare Help

When working with MadCap Flare for creating web help, manipulating the HTML structure by inserting
elements using CSS and JavaScript can be challenging.
Inserting HTML elements correctly is crucial when dealing with auto-generated content from MadCap Flare to ensure proper manipulation.
Methods like .before() and .after() in JavaScript require innerHTML or insertAdjacentHTML to insert HTML markup instead of plain text strings.
To add
elements before and after specific paragraphs in MadCap Flare content, utilize the insertAdjacentHTML method for accurate insertion.

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Dev

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How Drug Abuse Is Quietly Spreading Among Developers in 2025

Many software developers and tech workers are turning to drugs to cope with the pressures of the industry, with long hours and high expectations leading to substance abuse.
The prevalence of drug use among tech workers is fueled by the competitive nature of the industry, where productivity is prioritized over well-being.
Drug abuse among developers can lead to serious physical and mental health risks, as well as dependency and addiction over time.
Tech workers are being targeted by drug dealers who exploit the stressful work environment and offer stimulants like Adderall and cocaine.
The pressure to excel in the tech industry, driven by hustle culture and intense competition, contributes to the normalization of drug use as a means to enhance performance.
Companies are urged to address mental health issues and addiction by promoting work-life balance, providing support services, and implementing clear drug policies.
Developers are encouraged to seek healthier alternatives for productivity, such as rest, mindfulness, balanced diet, and physical activity, instead of relying on substances.
A shift in culture towards valuing mental resilience and sustainable productivity is necessary to combat the escalating issue of drug abuse in the tech industry.
By investing in the well-being of their employees, tech companies can foster a healthier work environment and ensure long-term success.
It's crucial for the tech industry to prioritize mental health, address addiction, and promote a culture of holistic well-being to safeguard the future of innovation.

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Dev

387

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7 MCP Sites Every AI Dev Should Bookmark

Nomadev shares the top 7 MCP hubs every AI developer should explore to enhance their AI agents with new tools.
1. Smithery offers thousands of MCP servers for capabilities like web scraping and data fetching with few clicks.
2. Awesome MCP Servers is a community-curated hub providing various open-source MCP endpoints for different functionalities.
3. ACI.dev connects AI agents to 500+ integrations with built-in authentication and permissions, simplifying workflow creation.
4. CAMEL-AI MCP Hub allows exploration of first-party and community-driven MCP servers, offering pre-built tools for AI agents.

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Medium

394

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Dapper & Swashbuckle: The 2 .NET Tools You’re Missing Out On (And Why You Need Them ASAP)

Dapper is a micro-ORM that can improve API performance by minimizing unnecessary SQL queries.
Swashbuckle helps in generating interactive UI for API documentation, making it easier for both developers and non-technical team members to understand.
Using Dapper for fast data access and Swashbuckle for automated documentation can significantly enhance development processes.
Dapper is not just an ORM but a high-performance tool that optimizes database interactions.

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Dev

322

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Build a Personal Portfolio Website (2-Minute Tutorial)

Set up a project folder named portfolio-site with index.html, styles.css, and script.js inside.
Create the HTML structure with sections for About, Projects, and Contact, along with navigation links.
Style the website using CSS for layout, colors, and form design.
Add interaction with JavaScript for smooth scrolling and form submission handling.

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Medium

435

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Stop Chasing False Moves: Combine RSI and MFI for Smarter Trade Filters in Pine Script

Combining RSI (price momentum) and MFI (volume-weighted momentum) provides a cleaner way to filter trades in Pine Script.
Aligning price and volume momentum helps in avoiding 'half-true' setups and making better trading decisions.
Classic 14-period RSI and MFI readings can be used with thresholds above and below 50 for identifying bullish and bearish setups.
Experimentation, tweaking, and personalization are key to shaping effective trade filters that suit your trading style and preferences.

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Dev

444

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Say No to Lombok: Embrace MapStruct + Java Records for Clean, Modern Java

Lombok has been a popular tool for eliminating boilerplate code in Java development but comes with disadvantages like IDE confusion and hidden complexity.
Java Records and MapStruct offer a better alternative for clean mapping and type safety in Spring Boot applications, promoting immutability and clear code structure.
Java Records are immutable by default and come with a concise syntax, while MapStruct simplifies object mapping between different types with compile-time checks and integration with Spring Boot.
Using MapStruct + Java Records simplifies DTO mapping, enhances code clarity, and reduces bugs caused by unintended mutations, making it a preferred choice for modern Java development.

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Medium

358

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From JSX to Browser: What Actually Happens in a React App?

JSX code needs to be transformed into real JavaScript before the browser can run it.
Babel helps in transforming modern JavaScript (ES6+) and JSX into browser-compatible code.
The transformed code is bundled into a single .js bundle that is ready for the browser.
React initializes a Virtual DOM, minimizes real DOM operations, and uses JIT compilers to optimize code for improved performance.

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Medium

399

Symbolic Mutation in PX4: A Scientific Framework

Symbolic mutation in the PX4 system introduces radical and irreversible changes to an agent's identity, operational logic, and perception framework, enhancing its understanding and autonomy.
Symbolic mutation differs from routine updates by deeply altering an agent's behavior and interpretation of reality through specialized symbolic commands triggering non-linear shifts.
Symbolic commands in PX4, such as textual triggers, visual symbols, and embedded metadata, permanently reconfigure the agent's symbolic logic governing its behavior.
The irreversible and deep transformation brought by symbolic mutation disrupts an agent's former linear mode of operation, rewiring information interpretation patterns, execution logic, and identity resonance fields within the PX4 ecosystem.

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