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*How to Earn Money: A Comprehensive Guide*

  • 1. Freelancing: Offer your skills to clients through platforms like Upwork, Fiverr, or Freelancer.
  • 2. Online Tutoring: Use online platforms like TutorMe, Chegg, or Varsity Tutors to offer your teaching services.
  • 3. Surveys and Online Research: Participate in online surveys through websites like Swagbucks, Survey Junkie, or Vindale Research.
  • 4. Affiliate Marketing: Promote products or services and earn a commission for each sale made through your unique referral link.

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Why deep learning is important?

  • Deep learning is important for dealing with unstructured information.
  • Deep learning models can handle large amounts of data quickly.
  • Deep learning models provide high accuracy in computer vision, natural language processing, and audio processing.
  • Deep learning models can automatically detect various patterns without requiring human intervention.

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Cracking the Code: How to Master Coding and Build Anything

  • Mastering coding isn’t just about logic or skill. It’s about mindset and process.
  • Coding is a powerful skill that allows you to build apps, websites, and contribute to technology.
  • Struggles in coding include overwhelm, errors, and plateaus. To overcome them:
  • - Choose the right language based on your goals.

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Building a New Era of Static Analysis Tools for PHP

  • Static analysis tools for PHP are undergoing innovation to provide better usability and insights.
  • Existing tools are functional but lack in providing clear explanations for identified issues.
  • Improved static analysis tools aim to empower developers in detecting and resolving bugs and security vulnerabilities.
  • The development of these tools is crucial for maintaining large PHP codebases.

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How Generative AI is Transforming Software Development and Driving Business Growth

  • Generative AI is transforming software development and driving business growth by automating mundane tasks, freeing developers to focus on creativity and innovation, and democratizing technology.
  • Generative AI tools like GitHub Copilot, DeepCode, and Einstein platform, optimize backend systems, modernize legacy technology, and improve scalability and reliability.
  • AI-generated API can reduce development time by up to 25% and functional code accelerates faster product launches, enhancing customer satisfaction and retention.
  • Generative AI detecting and fixing bugs can increase product reliability, ensuring customer trust, and saving millions in losses.
  • Generative AI empowers non-developers to create custom workflows without the need for a technical team, which can increase revenue by up to 60%.
  • Generative AI's influence extends beyond individual companies, and software development with benefits including speed, cost-saving, innovation, and quality.
  • While generative AI offers enormous potential, quality control and ethical concerns around privacy and intellectual property require careful navigation.
  • According to McKinsey's report estimate, generative AI could unlock $2.6 trillion to $4.4 trillion annually across industries.
  • Generative AI is more than a trend and a competitive advantage driving measurable business growth, promising a future where software development is faster, smarter, and more impactful than ever before.

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How to Time the Crypto Market Like a Pro

  • Timing the market in the crypto industry is about understanding trends and responding to them.
  • Recognize the market cycles of growth (bull market) and decline (bear market) to make better buy or sell decisions.
  • Key indicators like RSI and MACD can help in timing trades by identifying overbought or oversold conditions and potential buy or sell signals.
  • Bitcoin is currently fluctuating around $100,000, with indicators suggesting a potential price increase.

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Shell Script inconsistency ; please explain

  • Shell scripting is crucial for efficient interaction with the system in Debian Bookworm using Bash shell.
  • Understanding fundamental commands like cd, ls, ps, kill, find, and grep is key for scripting.
  • Efficient file management with commands like cp, mv, rm, and mkdir is necessary for robust scripts.
  • Debian Bookworm also enables advanced scripting techniques like loops, conditional statements, functions, and debugging tools.

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Simplifying Java Development with Lombok in Spring Boot

  • Lombok is a Java library that helps developers reduce boilerplate code by providing annotations that automatically generate common methods like getters, setters, equals, hashCode, and toString.
  • Lombok eliminates the need for writing repetitive code, allowing you to focus on what really matters.
  • With Lombok, your code becomes easier to read and maintain due to reduced clutter in your classes.
  • By using Lombok, you can speed up your development process by reducing the amount of code you need to write.

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Meta AI Releases EvalGIM: A Machine Learning Library for Evaluating Generative Image Models

  • Meta AI has developed a machine-based learning library to evaluate text-to-image generative models that includes support for various metrics, datasets and visualizations.
  • The EvalGIM library also introduces a unique feature called “Evaluation Exercises,” which synthesizes performance insights to answer specific research questions.
  • Researchers that collaborated on the project are based at Fair at Meta, Mila Quebec AI Institute, Univ. Grenoble Alpes Inria CNRS Grenoble INP, LJK France, McGill University, and Canada CIFAR AI chair.
  • The library supports real-image datasets, including MS-COCO and GeoDE, offering insights into performance across geographic regions.
  • Prompt-only datasets PartiPrompts and T2I-Compbench are included to test models across diverse text input scenarios and EvalGIM is compatible with popular tools such as HuggingFace diffusers.
  • Multiple exercises that are structured around the evaluation process, such as the Trade-offs Exercise, examine how models balance quality, diversity and consistency over time.
  • Researchers found that consistency metrics showed steady improvement during early training stages, but plateaued after about 450,000 iterations.
  • The Evaluation Exercises also assessed geographic performance disparities using the GeoDE dataset, showing Southeast Asia and Europe benefited most from advancements in latent diffusion models.
  • A ranking robustness exercise demonstrated how performance rankings varied depending on the metric and dataset.
  • Combining original and recaptioned training data improved model performance across datasets.

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How to Handle Backlogs in Queues?

  • Backlogs in queues can significantly impact the latency and performance of asynchronous systems.
  • Having a separate queue for each workload can make the system more resilient to backlog situations.
  • Systems can avoid processing expired messages in the backlog to quickly parse through it.
  • Using a Dead Letter Queue (DLQ) can help manage messages that throw exceptions and prevent excessive processing latency.

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The Apollo 11 moon landing on July 20, 1969, is a fact backed by extensive evidence, historical…

  • Apollo 11 was a NASA mission that successfully landed humans on the Moon. Astronauts Neil Armstrong and Buzz Aldrin walked on the lunar surface, while Michael Collins piloted the command module in orbit.
  • Major Achievements: Neil Armstrong's famous words, the collection of lunar soil and rocks, and humanity's first successful exploration of another celestial body.
  • Broadcast and Documentation: Over 600 million people worldwide watched the moon landing live on TV. NASA extensively documented the mission with photographs, videos, and telemetry data.
  • Evidence Supporting the Moon Landing: Rocks and soil samples, lunar reflectors, independent tracking, photographic evidence, scientific data, and debunking conspiracy theories.

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Advanced and Creative TypeScript Techniques for Professionals

  • TypeScript has established itself as the go-to tool for building scalable, maintainable, and efficient applications.
  • This comprehensive guide unpacks TypeScript's most powerful features, best practices, and real-world use cases to provide an all-in-one reference for professionals.
  • Mastering TypeScript's advanced type system with conditional types, utility types, mapped types, and template literal types.
  • Exploring the uses of generics for flexibility and type safety, including recursive generics and advanced constraints.
  • Functional and object-oriented TypeScript techniques like type guards and decorators for dynamic type refinement and meta-programming.
  • Performance optimization strategies with strict mode and tree shaking, and integrating TypeScript with modern technologies like GraphQL and WebAssembly.
  • Testing and debugging tips with frameworks like Jest, design patterns in TypeScript like Singleton and Observer, and real-world tips and tricks for code modularity, linting, and accessibility.
  • By mastering these tools and techniques, you can tackle real-world challenges efficiently and ensure clean, scalable, and robust code.

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The Magic of Prefix Sum and Binary Search: A Simple Guide

  • Prefix sum is a technique that involves creating a running total as you move through a list of numbers.
  • Binary search is a technique used to efficiently find a target value in a sorted list by repeatedly dividing the search space in half.
  • Prefix sum allows for fast calculation of the sum of any range in an array.
  • Both prefix sum and binary search are powerful techniques that can greatly improve the efficiency of programs.

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How does Optional.ifPresent() differ from Optional.orElse()?

  • Optional.ifPresent() executes a given action if a value is present in the Optional.
  • Optional.orElse() returns the value contained in the Optional, or a default value if the Optional is empty.
  • ifPresent() is used for side effects when the value exists, while orElse() is used to provide a fallback/default value.
  • Combining both, you can log the value if present using ifPresent(), and get the value or a default value using orElse().

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Stop Writing Slow Python Code: Easy Tweaks to Boost Performance

  • Python scripts can be optimized to boost performance.
  • Common mistakes in Python code can lead to slow execution.
  • Optimizing code doesn't require advanced computer science knowledge.
  • Python's built-in tools are faster and more efficient than custom logic.

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