TJS Articles & News

Stop Writing Spaghetti if-else Chains: Parsing JSON with Python’s match-caseTowards Data Science Introduction If you work in data science, data engineering, or as as a frontend/backend developer, you deal with JSON. For professionals, its basically only death, taxes, and JSON-parsing that is inevitable. The issue is that parsing JSON is often a serious pain. Whether you are pulling data from a REST API, parsing logs, or reading
The post Stop Writing Spaghetti if-else Chains: Parsing JSON with Python’s match-case appeared first on Towards Data Science.

 Introduction If you work in data science, data engineering, or as as a frontend/backend developer, you deal with JSON. For professionals, its basically only death, taxes, and JSON-parsing that is inevitable. The issue is that parsing JSON is often a serious pain. Whether you are pulling data from a REST API, parsing logs, or reading
The post Stop Writing Spaghetti if-else Chains: Parsing JSON with Python’s match-case appeared first on Towards Data Science. Read More  

CEOs still betting big on AI: Strategy vs. return on investment in 2026AI News Enterprise leaders are pressing ahead with artificial intelligence, even as some early results remain uneven. Reporting from the Wall Street Journal and Reuters shows that most CEOs expect AI spending to keep rising through 2026, despite difficulty tying those investments to clear, enterprise-wide returns. The tension highlights where many organisations now sit in their AI
The post CEOs still betting big on AI: Strategy vs. return on investment in 2026 appeared first on AI News.

 Enterprise leaders are pressing ahead with artificial intelligence, even as some early results remain uneven. Reporting from the Wall Street Journal and Reuters shows that most CEOs expect AI spending to keep rising through 2026, despite difficulty tying those investments to clear, enterprise-wide returns. The tension highlights where many organisations now sit in their AI
The post CEOs still betting big on AI: Strategy vs. return on investment in 2026 appeared first on AI News. Read More  

EpiPlanAgent: Agentic Automated Epidemic Response Planningcs.AI updates on arXiv.org arXiv:2512.10313v2 Announce Type: replace
Abstract: Epidemic response planning is essential yet traditionally reliant on labor-intensive manual methods. This study aimed to design and evaluate EpiPlanAgent, an agent-based system using large language models (LLMs) to automate the generation and validation of digital emergency response plans. The multi-agent framework integrated task decomposition, knowledge grounding, and simulation modules. Public health professionals tested the system using real-world outbreak scenarios in a controlled evaluation. Results demonstrated that EpiPlanAgent significantly improved the completeness and guideline alignment of plans while drastically reducing development time compared to manual workflows. Expert evaluation confirmed high consistency between AI-generated and human-authored content. User feedback indicated strong perceived utility. In conclusion, EpiPlanAgent provides an effective, scalable solution for intelligent epidemic response planning, demonstrating the potential of agentic AI to transform public health preparedness.

 arXiv:2512.10313v2 Announce Type: replace
Abstract: Epidemic response planning is essential yet traditionally reliant on labor-intensive manual methods. This study aimed to design and evaluate EpiPlanAgent, an agent-based system using large language models (LLMs) to automate the generation and validation of digital emergency response plans. The multi-agent framework integrated task decomposition, knowledge grounding, and simulation modules. Public health professionals tested the system using real-world outbreak scenarios in a controlled evaluation. Results demonstrated that EpiPlanAgent significantly improved the completeness and guideline alignment of plans while drastically reducing development time compared to manual workflows. Expert evaluation confirmed high consistency between AI-generated and human-authored content. User feedback indicated strong perceived utility. In conclusion, EpiPlanAgent provides an effective, scalable solution for intelligent epidemic response planning, demonstrating the potential of agentic AI to transform public health preparedness. Read More  

The Skills That Bridge Technical Work and Business ImpactTowards Data Science In the Author Spotlight series, TDS Editors chat with members of our community about their career path in data science and AI, their writing, and their sources of inspiration. Today, we’re thrilled to share our conversation with Maria Mouschoutzi.  Maria is a Data Analyst and Project Manager with a strong background in Operations Research, Mechanical
The post The Skills That Bridge Technical Work and Business Impact appeared first on Towards Data Science.

 In the Author Spotlight series, TDS Editors chat with members of our community about their career path in data science and AI, their writing, and their sources of inspiration. Today, we’re thrilled to share our conversation with Maria Mouschoutzi.  Maria is a Data Analyst and Project Manager with a strong background in Operations Research, Mechanical
The post The Skills That Bridge Technical Work and Business Impact appeared first on Towards Data Science. Read More  

The Machine Learning “Advent Calendar” Day 14: Softmax Regression in ExcelTowards Data Science Softmax Regression is simply Logistic Regression extended to multiple classes.
By computing one linear score per class and normalizing them with Softmax, we obtain multiclass probabilities without changing the core logic.
The loss, the gradients, and the optimization remain the same.
Only the number of parallel scores increases.
Implemented in Excel, the model becomes transparent: you can see the scores, the probabilities, and how the coefficients evolve over time.
The post The Machine Learning “Advent Calendar” Day 14: Softmax Regression in Excel appeared first on Towards Data Science.

 Softmax Regression is simply Logistic Regression extended to multiple classes.
By computing one linear score per class and normalizing them with Softmax, we obtain multiclass probabilities without changing the core logic.
The loss, the gradients, and the optimization remain the same.
Only the number of parallel scores increases.
Implemented in Excel, the model becomes transparent: you can see the scores, the probabilities, and how the coefficients evolve over time.
The post The Machine Learning “Advent Calendar” Day 14: Softmax Regression in Excel appeared first on Towards Data Science. Read More  

Lessons Learned from Upgrading to LangChain 1.0 in ProductionTowards Data Science What worked, what broke, and why I did it
The post Lessons Learned from Upgrading to LangChain 1.0 in Production appeared first on Towards Data Science.

 What worked, what broke, and why I did it
The post Lessons Learned from Upgrading to LangChain 1.0 in Production appeared first on Towards Data Science. Read More  

Walmart’s AI strategy: Beyond the hype, what’s actually workingAI News Walmart’s December 9 transfer to Nasdaq wasn’t just a symbolic gesture. The US$905 billion retailer is making its boldest claim yet: that it’s no longer a traditional discount chain, but a tech-powered enterprise using AI to fundamentally rewire its retail operations. But beyond the marketing spin and the parade of AI announcements, what’s genuinely transforming
The post Walmart’s AI strategy: Beyond the hype, what’s actually working appeared first on AI News.

 Walmart’s December 9 transfer to Nasdaq wasn’t just a symbolic gesture. The US$905 billion retailer is making its boldest claim yet: that it’s no longer a traditional discount chain, but a tech-powered enterprise using AI to fundamentally rewire its retail operations. But beyond the marketing spin and the parade of AI announcements, what’s genuinely transforming
The post Walmart’s AI strategy: Beyond the hype, what’s actually working appeared first on AI News. Read More  

Deep-learning model predicts how fruit flies form, cell by cellMIT News – Machine learning The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.

 The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease. Read More