Mert Ersoz's article reveals how Dynamic Inventory Optimization with Bayesian learning (and the powerful Knowledge Gradient policy) helps businesses navigate censored demand for superior long-term performance.

How do you make your voice assistant TRULY understand complex queries, accents, and background noise? 🤔 Heiko Hotz unpacks Automated Prompt Engineering, a systematic approach to optimizing function calls for real-world voice AI.

What if you had a 24/7 assistant for your data science tasks? Sara Nobrega shares some of her favorite prompts & tricks for leveraging LLMs in planning, data cleaning, and EDA, ensuring you get useful, non-generic answers.

How Jens Winkelmann built an AI-powered prototype to turn images into insights.

Himalaya Bir Shrestha's insightful article reveals how viewing problems from both primal and dual perspectives can simplify complex LPs, helping you elegantly navigate the trade-off between maximizing revenue and minimizing resource constraints.

Unlock the hidden logic of matrix operations. Tigran Hayrapetyan's article, Part 3 of a series, uses a unique "X-way interpretation" and "horizontal flip" analogy to intuitively explain matrix transpose and demystify its properties.

Unlock the future of numerical computation. @taupirho unveils @NVIDIA's cuNumeric, promising massive performance boosts for your existing NumPy code by leveraging the power of GPUs. Read the full article FREE now and supercharge your data science workflows.

.@EivindKjos breaks down the essential techniques for Context Engineering: from zero-shot and dynamic few-shot prompting to leveraging RAG and tools (MCP!) for superior LLM performance.

Alessio Tamburro dives into experiments with GPT4 (vision) and o3-mini on abstract grid transformation tasks, showing impressive algorithm synthesis but also the fragility of generalization.

Stop LLMs from hallucinating real-time data. Iqbal Rahmadhan shows you how to equip your AI agent with API tools (using Open-Meteo) to retrieve accurate, up-to-date information.

📣 Calling all Data Scientists and ML Engineers 📣 Our first ever eBook, thanks to @plotlygraphs, dives into a more fluid, expressive development cycle for data apps, showing how AI empowers teams to accelerate their builds. Download NOW 👉

From the Hotel California in Paris to the Manhattan Hotel in Jakarta. 🌍 . Anna Gordun Peiro uses GeoPandas and custom API calls to explore the most "borrowed" city names in hotels worldwide.

Struggling to future-proof your data career? Marina Tosic reveals how clarifying your core values and embracing constant change (hint: job security is about adaptability, not an illusion) can build resilience and unlock unexpected opportunities.

Struggling to categorize a mountain of unlabeled data? Alex Davis delivers a practical Python tutorial showing you how to use LLM-based topic labeling with GPT-4o-mini.

If your @PyTorch gradients are throwing surprises, you’re not alone. Maciej Mikulski dives into what actually happens under the hood.

Build your own AI-powered web app! @GongDestin's article is your practical guide to creating an interactive MCP client with @Streamlit, connecting to remote servers like DeepWiki and @HuggingFace for diverse AI functionalities.

What does it REALLY take to build a multi-agent system? @sravani_alle's SQL assistant demo shows how to bring AI agents to life while staying grounded in real-world engineering constraints.

📈 TRENDING 📈 Hailey Quach dives into the real-world challenges of AI agent infrastructure & communication protocols, unpacking how to tackle the complexities of multi-agent systems in production. Want to share your expertise on this topic? Submit your article to Towards Data.

Don't just build, think about HOW you build with AI. Stephanie Kirmer shares her perspective on LLMs in coding, arguing for development that nurtures talent and ensures long-term code quality.

LLMs don't learn post-training. or do they? Julian Mendel's article unpacks the nuances of LLM learning, creativity, and emotion, referencing cutting-edge research that challenges common beliefs.