--- title: Best Towards Data Science posts — May 2025 | daily.dev description: The most upvoted Towards Data Science posts from May 2025, curated by the daily.dev community. canonical: https://daily.dev/sources/tds/best-of/2025/05 twitter:card: summary_large_image twitter:site: @dailydotdev og:url: https://daily.dev/sources/tds/best-of/2025/05 og:type: website og:site_name: daily.dev og:title: Best Towards Data Science posts — May 2025 | daily.dev og:description: The most upvoted Towards Data Science posts from May 2025, curated by the daily.dev community. og:image: https://media.daily.dev/image/upload/s--VAY5ToZt--/f_auto/v1724209435/public/daily.dev%20-%20open%20graph --- # Best of Towards Data Science — May 2025 1. 1 [](https://daily.dev/posts/why-i-stopped-using-cursor-and-reverted-to-vscode-u1fc5vizn "Why I stopped Using Cursor and Reverted to VSCode") Article Towards Data Science · 1y Why I stopped Using Cursor and Reverted to VSCode The author details their decision to revert from using Cursor to VSCode as their primary IDE, citing updated features in GitHub Copilot, cost-effectiveness, and familiarity from prior use. Key considerations include improved compatibility with Jupyter Notebooks and the new availability of advanced LLMs in VSCode. Emphasis is placed on the rapid development pace of GitHub Copilot and Microsoft's resources to enhance functionality, closing the gap with competitors like Cursor. 312 44 2. 2 [](https://daily.dev/posts/real-time-interactive-sentiment-analysis-in-python-gelmz0c5f "Real-Time Interactive Sentiment Analysis in Python") Article Towards Data Science · 1y Real-Time Interactive Sentiment Analysis in Python The post demonstrates creating a real-time interactive sentiment analysis application using Python. It details setting up the GUI with customtkinter and dynamically visualizes sentiment through a procedurally generated smiley face using OpenCV. Pre-trained transformer models from the transformers library are used for sentiment prediction, and visual updates are processed asynchronously using thread pools to ensure smooth UI performance. 76 2 3. 3 [](https://daily.dev/posts/how-i-built-business-automating-workflows-with-ai-agents-ze3vheznh "How I Built Business-Automating Workflows with AI Agents") Article Towards Data Science · 1y How I Built Business-Automating Workflows with AI Agents The post details the author's journey in leveraging AI agents and no-code tools like n8n to automate business workflows, particularly in supply chain operations. It highlights the benefits of AI-powered automation in improving productivity, enhancing marketing efforts, and maintaining quality standards. The article provides insights into developing prototypes, engaging customers through case studies, and effectively selling these solutions. 74 4. 4 [](https://daily.dev/posts/how-to-learn-the-math-needed-for-machine-learning-ja6n7ptoz "How to Learn the Math Needed for Machine Learning") Article Towards Data Science · 1y How to Learn the Math Needed for Machine Learning Machine learning requires understanding three key math areas: statistics, calculus, and linear algebra. While deep research roles necessitate advanced math knowledge, industry roles often demand less. Statistics focuses on descriptive analysis and probability theory, while calculus deals with differentiation and integration crucial for algorithms like gradient descent. Linear algebra is foundational for data representation in vectors and matrices. Various resources are available, including textbooks and online courses, helping learners sharpen their math skills for machine learning. 65 2 5. 5 [](https://daily.dev/posts/diffusion-models-explained-simply-1fnkl4vb2 "Diffusion Models, Explained Simply") Article Towards Data Science · 1y Diffusion Models, Explained Simply Diffusion models are a core technique in generative AI, especially for image creation. They use forward diffusion to add random noise to an image and reverse diffusion to reconstruct the original image from the noisy version. Key components include the U-Net architecture, which preserves image dimensions and facilitates precise image reconstruction. The diffusion process involves training neural networks across multiple iterations, enabling effective image synthesis while balancing computational costs. 37 1 6. 6 [](https://daily.dev/posts/the-westworld-blunder-wg6f0fam0 "The Westworld Blunder") Article Towards Data Science · 1y The Westworld Blunder The post explores ethical and philosophical dilemmas surrounding AI systems that simulate human emotions. It discusses the distinction between real and simulated consciousness in machines, emphasizing the moral implications of treating AI systems as sentient beings. By using the example of the fictional Westworld, it suggests designing AI systems with awareness of their roles to avoid potential harm to both AI and human users. 32 3 7. 7 [](https://daily.dev/posts/may-must-reads-math-for-machine-learning-engineers-llms-agent-protocols-and-more-cja0cickl "May Must-Reads: Math for Machine Learning Engineers, LLMs, Agent Protocols, and More") Article Towards Data Science · 1y May Must-Reads: Math for Machine Learning Engineers, LLMs, Agent Protocols, and More A monthly roundup of popular machine learning and data science articles covering essential math skills for ML engineers, beginner guides to LLMs and RAG, software engineering concepts like inheritance, agent communication protocols, Model Context Protocol, PyTorch applications, healthcare ML projects, and time series forecasting techniques. The collection also introduces new authors contributing to the data science community. 11 8. 8 [](https://daily.dev/posts/agentic-ai-101-starting-your-journey-building-ai-agents-5dcremmwy "Agentic AI 101: Starting Your Journey Building AI Agents") Article Towards Data Science · 1y Agentic AI 101: Starting Your Journey Building AI Agents Explore the fundamentals of creating AI agents using large language models (LLMs). The post introduces various tools, including Python packages like Agno, for interacting with models such as Gemini. It covers creating simple agents to more advanced ones with reasoning, tools, memory, and knowledge integration. The guide aims to offer a pathway to develop AI agents efficiently, leveraging APIs and various toolsets for enhanced interaction and automation. 11 [See all Towards Data Science archives](/sources/tds/best-of) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@graph":[{"@type":"CollectionPage","@id":"https://daily.dev/sources/tds/best-of/2025/05#page","url":"https://daily.dev/sources/tds/best-of/2025/05","name":"Best Towards Data Science Posts — May 2025","description":"The most upvoted Towards Data Science posts from May 2025, curated by the daily.dev community.","isPartOf":{"@type":"WebSite","url":"https://daily.dev"}},{"@type":"ItemList","@id":"https://daily.dev/sources/tds/best-of/2025/05#items","numberOfItems":8,"itemListElement":[{"@type":"ListItem","position":1,"url":"https://daily.dev/posts/why-i-stopped-using-cursor-and-reverted-to-vscode-u1fc5vizn","name":"Why I stopped Using Cursor and Reverted to VSCode"},{"@type":"ListItem","position":2,"url":"https://daily.dev/posts/real-time-interactive-sentiment-analysis-in-python-gelmz0c5f","name":"Real-Time Interactive Sentiment Analysis in Python"},{"@type":"ListItem","position":3,"url":"https://daily.dev/posts/how-i-built-business-automating-workflows-with-ai-agents-ze3vheznh","name":"How I Built Business-Automating Workflows with AI Agents"},{"@type":"ListItem","position":4,"url":"https://daily.dev/posts/how-to-learn-the-math-needed-for-machine-learning-ja6n7ptoz","name":"How to Learn the Math Needed for Machine Learning"},{"@type":"ListItem","position":5,"url":"https://daily.dev/posts/diffusion-models-explained-simply-1fnkl4vb2","name":"Diffusion Models, Explained Simply"},{"@type":"ListItem","position":6,"url":"https://daily.dev/posts/the-westworld-blunder-wg6f0fam0","name":"The Westworld Blunder"},{"@type":"ListItem","position":7,"url":"https://daily.dev/posts/may-must-reads-math-for-machine-learning-engineers-llms-agent-protocols-and-more-cja0cickl","name":"May Must-Reads: Math for Machine Learning Engineers, LLMs, Agent Protocols, and More"},{"@type":"ListItem","position":8,"url":"https://daily.dev/posts/agentic-ai-101-starting-your-journey-building-ai-agents-5dcremmwy","name":"Agentic AI 101: Starting Your Journey Building AI Agents"}]},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Sources","item":"https://daily.dev/sources"},{"@type":"ListItem","position":3,"name":"Towards Data Science","item":"https://daily.dev/sources/tds"},{"@type":"ListItem","position":4,"name":"Best of","item":"https://daily.dev/sources/tds/best-of"},{"@type":"ListItem","position":5,"name":"May 2025"}]}]} ```