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Automating Tableau Cloud Backups with Python, REST API and AWS

  • Automating Tableau Cloud backups using Python, REST API, and AWS provides peace of mind and flexibility for handling unintentional changes or data loss.
  • Technologies used include a general-purpose scripting language, AWS Lambda for serverless execution, and Amazon S3 for storage.
  • The process involves triggers from Amazon EventBridge activating an AWS Lambda function to interact with Tableau Cloud via the REST API.
  • Backups are stored in Amazon S3 in an organized manner for easy access and management.
  • Preparation steps involve creating a Personal Access Token in Tableau Cloud and configuring AWS Secrets Manager for secure storage of credentials.
  • Creating a new bucket in Amazon S3 and setting up an AWS Lambda function are also necessary steps.
  • Dependencies need to be packaged with Python scripts for AWS Lambda as it doesn't allow runtime library installation.
  • Environment variables can be defined for configuration in the AWS Lambda console.
  • Automating backups can be achieved using Amazon EventBridge to run backups on a scheduled basis.
  • Accessing logs post-execution helps in verifying the correctness of the backup process.

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Building a Feature Flag System in Node.js with Redis and Middleware

  • Feature flags (also known as feature toggles) allow you to enable or disable functionality without deploying new code.
  • This article explains how to implement a feature flag system in Node.js using Redis and Express middleware.
  • It provides step-by-step instructions for project setup, Redis client setup, middleware implementation, and usage in routes.
  • The article also suggests enhancements like enabling features for specific user IDs or roles, implementing flag variants for A/B testing, creating a dashboard for toggling flags, and using JSON structures in Redis for more complex rules.

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3 Mistakes You’re Probably Making When Learning to Code on Your Own

  • Learning to code on your own can be overwhelming
  • One common mistake is switching programming languages too frequently
  • Another mistake is not focusing on small, practical projects
  • Lack of support and guidance can also hinder progress

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What is AI, Really?

  • AI is an umbrella term encompassing various concepts and models related to human intelligence tasks.
  • The history of AI dates back to the 1950s, with a formal field beginning at the Dartmouth Conference in 1956.
  • AI has experienced waves of hype and progress, with notable milestones like IBM's Deep Blue and AlphaGo victories.
  • AI operates based on learning from data, where supervised learning involves teaching models patterns from training data.
  • Linear regression is a simple machine learning model that predicts data points' relationships.
  • The learning process involves using a loss function to measure errors and adjusting parameters through gradient descent.
  • AI subfields include machine learning, deep learning, and generative AI, each tailored for specific tasks.
  • AI systems can exhibit intelligence through problem-solving and pattern recognition but lack true understanding, feelings, or consciousness.
  • Models like ChatGPT generate responses based on statistical likelihoods rather than true comprehension.
  • AI is synthetic intelligence, mimicking human thinking without replicating consciousness, relying on math and data for operations.

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What Happens to sessionStorage When You Duplicate a Tab?

  • When you duplicate a tab, sessionStorage is copied into the new tab.
  • After duplication, each tab maintains its own version of sessionStorage.
  • sessionStorage does not propagate changes between tabs, even duplicated ones.
  • If your app logic depends on sessionStorage, be cautious about assumptions as duplicated tabs might carry over sensitive state unintentionally.

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Creating a simple access middleware for nextjs route handlers

  • The author created a simple access middleware for Next.js route handlers.
  • The author chose to build a wrapper function to add protection for specific endpoints.
  • The wrapper function checks if the user has the required permission to access the endpoint.
  • The author shared this as a tip for building simple demos.

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PHP 8.4’s array_find Function: Innovative and Practical, or Just a Nice-to-Have?

  • PHP 8.4 introduces array_find() function for elegant array searching.
  • The function allows developers to define custom search conditions using a closure.
  • Advantages include improved readability, flexibility, and consistency with functional paradigm.
  • Limitations include compatibility issues and learning curve for closure syntax.

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Discover How to Make Money in eLearning Today

  • The eLearning market is a lucrative industry, with a projected value of over $399 billion and set to reach $1 trillion.
  • Creating study aids, such as summaries, definitions, and practice exercises, can provide invaluable support to learners.
  • Platforms like Draft2Digital and Etsy offer alternative publishing avenues for reaching wider audiences.
  • The eLearning market offers ongoing opportunities as educational content needs evolve and demand for certifications increases.

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How I Turned $14.95 into a $500 Income Stream

  • Unlock the Secret to Passive Income with 12 Powerful AI Apps offers an opportunity to create a passive income stream.
  • For just $14.95, users gain access to a suite of 12 premium AI tools with a value of over $11,000.
  • The apps provide solutions for website creation, video marketing, and app development without requiring extensive technical skills.
  • Users can generate income and learn valuable skills while exploring new markets and expanding their business.

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OpenAI Developing AI Agent to Replace Software Engineers, CFO Says

  • OpenAI is creating an AI agent, called A-SWE, to automate the work of software engineers, handling tasks like quality assurance and documentation.
  • This AI agent is part of OpenAI’s efforts in developing agentic AI systems that work independently on behalf of users.
  • A-SWE follows the release of Cognition AI's Devin, the first AI software engineer in the market.
  • OpenAI's A-SWE is the third agentic tool, succeeding Deep Research and Operator, offering comprehensive research reports and web-based task performance.
  • The aim is for AI agents to create novel discoveries beyond human knowledge.
  • GPT-4.5, OpenAI's advanced model, is trained for emotional intelligence (EQ) in addition to technical skills.
  • Despite optimism towards AI colleagues, concerns about widespread job displacement from AI remain among human workers.
  • OpenAI is expanding to become an AI infrastructure provider and applications developer, emphasizing the importance of owning intellectual property.
  • The $500 billion Stargate project with SoftBank, Oracle, and MGX aims to build data centers for AI training and inference, ensuring sufficient computing power.
  • While OpenAI has seen rapid revenue growth and user engagement, an IPO is not immediate but remains a potential future step.

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Predicting Disease Categories Using TF-IDF, KNN & Streamlit

  • A disease prediction web app was developed using TF-IDF, KNN, and Streamlit.
  • The app uses a small medical dataset to predict disease categories based on user input.
  • TF-IDF is used to convert textual data into numeric feature vectors for machine learning.
  • The app is deployed using Streamlit Cloud and can be accessed through a live URL.

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OpenAI launches new GPT-4.1 series of language models for developers

  • OpenAI has launched the GPT-4.1 series of language models for developers.
  • GPT-4.1 is significantly better at coding tasks compared to its predecessor.
  • The series also includes GPT-4.1 mini and GPT-4.1 nano, with lower pricing and reduced capability.
  • GPT-4.1 models are designed to output only changed code lines, reducing costs and enhancing efficiency.

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The End of User Interfaces: Why Your AI Profile is the Future of Interaction

  • Interfaces are evolving rapidly as technology adapts to users, learning continuously from every interaction.
  • An AI companion that knows users' preferences, habits, and emotional states can act as a personalized interface for various tasks, such as booking a vacation.
  • The benefits of this approach include hyper-personalization, reduced cognitive load, enhanced privacy, and improved efficiency.
  • Challenges include trust in AI, ensuring transparency and accountability, and establishing interoperability standards.

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Back-End Data Serialization in Python: A Practical Comparison of SerializerMixin and Marshmallow

  • Marshmallow and SerializerMixin are used for data serialization in Python to convert model instances into JSON-friendly dictionaries.
  • SerializerMixin is simple and fast, suitable for prototyping or debugging, but can become messy when dealing with relationships or custom outputs.
  • Marshmallow allows developers to define schemas for explicit control over JSON serialization, providing features like automatic field generation, validation, and support for nested relationships.
  • For applications with complex data structures or specific needs, Marshmallow is a better option as it separates serialization logic from model logic and offers a consistent, readable structure.

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Render Only Above-Ground Entities in CesiumJS

  • Implement lazy loading or progressive loading techniques to load data as needed for better performance.
  • Utilize CesiumJS's built-in rendering features such as ClassificationType and level-of-detail rendering for efficient rendering.
  • Refer to the blog post 'Render Only Above-Ground Entities in CesiumJS' for techniques to render only above-ground entities.
  • Optimize performance using features like culling, frustum culling, and occlusion culling provided by CesiumJS.

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