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Towards Data Science

How To Build a Benchmark for Your Models

Building benchmarks for models is crucial in data science projects to evaluate performance accurately.
A benchmark consists of standardized metrics and simple baseline models for comparison.
By comparing models to benchmarks, improvements can be tracked reliably and performance assessed.
Creating benchmarks helps in setting clear objectives, enhancing client communication, and aiding in model selection.
Benchmarks also assist in detecting model drift, ensuring consistency across datasets, and providing immediate feedback.
Defining metrics, setting benchmarks, and running comparisons are key steps in building a benchmark for models.
Business-driven metrics like financial gain can be crucial in evaluating model performance for specific use cases.
The article provides examples of simple benchmarks like random model, majority model, simple XGB, and simple KNN.
Custom benchmarks tailored to specific business needs, such as customer churn scenarios, can also be designed.
While benchmarks are valuable, potential drawbacks include non-informative benchmarks, misinterpretation by stakeholders, and overfitting.

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Towards Data Science

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🚪🚪🐐 Lessons in Decision Making from the Monty Hall Problem

The Monty Hall Problem is a brain teaser offering lessons in Decision Making, especially relevant for data scientists.
The problem involves choosing between three doors, one with a prize and two with goats, and deciding whether to stick with the initial choice or switch.
By applying common sense, Bayesian analysis, and causal models, the optimal strategy is to always switch doors after the host reveals a goat.
Lessons learned from the Monty Hall Problem include the importance of updating beliefs with new information and shifting from fast to deep thinking.
The problem demonstrates the counterintuitive nature of probabilities and the need to be comfortable with ambiguity in decision-making.
Insights gained from the problem can be applied in real-world data science scenarios, emphasizing the value of critical thinking and subjective decision-making.
Various examples, analogies, visualizations, and simulations help elucidate the solution and enhance understanding of probability concepts.
The article concludes with a reflection on embracing ignorance, humility in learning, and the diverse approaches to problem-solving.
Overall, the Monty Hall Problem serves as a valuable tool for improving decision-making skills and thinking processes, particularly in data science.

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Dev

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5 developer tools to really step up your workflow

Lazygit is a TUI for git management, allowing easy changes, commits, and branch operations.
LazyDocker is a TUI manager for Docker, providing insights into running containers, available images, logs, metrics, and volumes.
Vim keybindings or using Neovim can enhance coding efficiency, especially with extensions in IDEs like VSCode for Vim support.
Obsidian is a note-taking tool with plugin support and note graph visualization, suitable for all users, and Tmux enables terminal multiplexing for efficient multitasking.

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Tech Radar

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Most job applicants use AI CV builder tools to get into work, and to my dismay, they say it is fair play

Many job applicants are using AI tools to write their CVs, with 53% admitting to using them.
AI-generated CVs often contain embellishments and false information, making it difficult for recruiters to differentiate from genuine submissions.
Despite concerns raised by 41% of applicants about AI giving some candidates an unfair advantage, the use of AI in job applications is becoming more prevalent.
Hiscox's Chief Underwriting Officer emphasized the need for cautious use of AI in the hiring process to avoid misleading employers and damaging relationships.

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Medium

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How I Optimized My React Application to Handle 3M+ Monthly Visitors

Implemented code splitting with React Lazy & Suspense to reduce initial load time and improve time-to-interactive.
Utilized caching and memoization techniques such as React.memo, useMemo, and useCallback to prevent unnecessary re-renders and reduce CPU cycles.
Optimized server-side rendering (SSR) with Next.js for SEO boost, faster content delivery, and reduced server load.
Integrated image and asset optimization strategies, lazy loading, and used a CDN with HTTP/2 for reduced latency and improved resilience.

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Medium

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Mastering Software Testing: A Simple Guide to Test Types for Beginners (and the Curious 50+)

Software testing explained in a simple and approachable manner.
The guide explores four essential categories of testing in plain English with examples.
Functional testing checks what the system does based on requirements while non-functional testing focuses on aspects like speed.
Learning test types and techniques ensures that software works well, consistently, and reliably for anyone interested in the field.

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Medium

Why I think Go is the best language for most orgs (and probably you as well)

The author shares their experience of transitioning from Java to Go while contributing to ArgoCD, highlighting the simplicity and speed of development in Go.
Go's minimal build processes, fast compile times, and clean dependency management streamline the development process and reduce friction, enabling quick PoC development and rapid debugging.
The short feedback loop and optimized development workflow in Go facilitate quick turnaround times, from writing code to deployment, contributing to increased productivity and faster incident resolution.
While acknowledging some drawbacks of Go, such as unlogged errors and differences in error handling compared to Java, the author emphasizes the benefits of Go's explicit and predictable error handling, leading to defensive and thoughtful code.

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Medium

376

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The End of High-Paying Tech Jobs? What Developers Need to Know

Tech job market, once offering high-paying roles, is undergoing a fundamental shift.
LinkedIn and Reddit reflect layoffs and pay level struggles among developers in 2025.
Shift from the era of abundant venture capital leading to bloated engineering teams.
Developers advised to adapt to the changing landscape of tech job market for survival.

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Image Credit: Fb

Introducing Pyrefly: A new type checker and IDE experience for Python

Pyrefly is an open source Python type checker and IDE extension written in Rust, focusing on ensuring type consistency and catching errors in code before execution.
It offers IDE integration and CLI usage for flexibility in workflow integration.
Developed in the open source community, Pyrefly aims to enhance Python's type system and libraries collaboratively.
Key steps to get started with Pyrefly include installing it via pip, migrating existing type checker configurations, and downloading the VSCode extension.
The project Pyre led to the creation of Pyrefly, with a focus on an extensible type checker that provides code navigation, scalability, and exporting types.
Pyrefly emphasizes performance, built in Rust for speed, and an IDE-first approach for consistent user experience.
The project also focuses on inference to benefit users from types even in unannotated code, promoting an open-source community and open development on GitHub.
Future plans for Pyrefly involve working with the Python community to enhance the language and developer experience, leveraging types for productivity and security.
Community collaboration is encouraged through feedback, bug reports, and contributions to further develop Pyrefly and expand its impact.
The release of Pyrefly as an alpha version is aimed at refining it for a stable release in the future, with an invitation for feedback and improvement suggestions.
The Meta team behind Pyrefly aims to illuminate bugs, enhance the Python development environment, and engage with the community through various platforms.

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Medium

376

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I Analyzed 100 Tech Lead Portfolios: These 5 Projects Are Red Flags to Recruiters

Analyzing 100 tech lead portfolios, certain projects consistently raised red flags for hiring managers and interviewers.
Red flags included over-engineered todo list apps, self-created frameworks, technology checklist projects, complex algorithm implementations, and straightforward clones of existing apps.
Recruiters often viewed over-engineered todo list apps as a sign of poor engineering judgment, preferring projects with real-world value and complexity.
Self-created frameworks, if neglected, raised concerns about stability and commitment, with recruiters valuing honesty about project maintenance.
Simply implementing trending technologies without relevance to the problem at hand signaled potential issues with prioritization and decision-making to recruiters.
Complex algorithm implementations without practical application could indicate a lack of focus on business impact, according to hiring managers.
Building clones of existing applications, without innovation or personal contribution, suggested a lack of creativity to recruiters.
Projects that impressed hiring managers included those enhancing developer workflows, performance optimization, open source contributions, and clear problem-solving with measurable outcomes.
Thoughtful performance analysis, consistent open source contributions, articulating business solutions, and completing side projects with clear scope were highly valued.
To strengthen a tech lead portfolio, focus on thoughtful documentation, demonstrating leadership qualities in projects, and maintaining transparency about project statuses.

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Medium

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Inside the Mechanics of JavaScript Symbol Properties

JavaScript introduced the Symbol type to create hidden property keys.
Symbols do not show up when objects are looped over or printed out.
To create a Symbol, the Symbol() function is used.
Symbols are unique with the same description strings yielding different values.
Symbols behave as object keys by being matched by identity.
Symbol properties are stored separately and do not mix with string keys.
Symbol keys are treated differently in property lookups and iterations.
Symbols are flagged as non-enumerable and skipped in common lookup methods.
Symbol properties can be accessed using Object.getOwnPropertySymbols().
Symbols are ideal for hiding data within objects and maintaining privacy.

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TechBullion

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Snapmaker Proudly Sponsors Printed World Conference 2025 in Amsterdam

Snapmaker sponsors Printed World Conference 2025 in Amsterdam, showcasing commitment to maker community and innovation.
The conference aims to bring together makers, designers, creators, and industry professionals for talks, workshops, and networking opportunities.
Snapmaker's sponsorship highlights dedication to supporting creators at all levels and fostering collaboration.
The event offers engaging speakers, workshops, and an exhibition area, promising an unforgettable experience for attendees.

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Pymnts

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Microsoft to Retire Bing Search APIs, Promote Azure AI Agents

Microsoft will retire Bing Search APIs on Aug. 11, as announced on Monday.
Customers are advised to consider using Grounding with Bing Search as an alternative, integrated with Azure AI Agents.
Grounding with Bing Search allows Azure AI Agents to incorporate real-time public web data in responses, focusing on chatbots.
The shift to AI-powered system is to meet market demand; Microsoft offers support for affected customers.

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Pcgamer

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YouTube's top brains crack making its ads even worse: Using AI to insert commercials at moments you're 'most engaged' with its videos

YouTube's top brains have developed a new system called 'Peak Points' utilizing Google's Gemini AI to identify the most engaging moments in videos for inserting ads.
Advertisers can leverage this feature to place ads at the 'most engaged' moments in videos, as identified by the AI, aiming for better audience engagement.
The concept of inserting ads at peak moments of viewer engagement raises concerns among users about intrusive advertising experiences and increased frustration.
Critics view this move as a profit-driven endeavor by Google, using AI as a buzzword to attract investors, while potentially worsening the user experience on the platform.

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Medium

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The Problem with Vibe Coding in Cursor

Passing through doorways and thresholds in various cultures signifies metaphysical boundaries and transitioning into a new mindset or focus.
The concept of 'vibe coding' involves utilizing AI assistance for coding, which can act as a psychological separator and lead to a different mode of reflection and analysis.
Working modularly with AI-generated code before integration can promote cleaner abstraction, better structure, and thoughtful coding practices.
While tools like Cursor offer seamless coding experiences, the act of switching between AI tools and coding spaces may enforce a deliberate mental structure and lead to better understanding and code quality.

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