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Why does Lasso do feature selection while Ridge just shrinks weights? The answer lies in L¹ vs L². Marco Hening Tallarico dives into the differences between these norms and their impact on model behavior in regression and beyond. towardsdatascience.com/from-a-point-t…

Ready to build smarter search with Knowledge Graphs & LLMs? Dylan Tartarini provides code and context for ingesting documents into @Neo4j and querying the graph using various strategies, including Cypher and enhanced RAG. towardsdatascience.com/build-query-kn…

Bridging the gap with clients starts with benchmarks. Lorenzo Mezzini's article explains how establishing clear baselines makes it easier to communicate model performance and demonstrate value to non-technical stakeholders. towardsdatascience.com/how-to-build-a…

📢 Coming Soon: How AI Is Shaping the Future of Data App Development Dashboards aren’t dead — but they are evolving. In our first-ever eBook, thanks to Plotly, Anne Bonner explores how AI is transforming data tools into reasoning engines that help users explore,

It's not just what you learn, but how you learn it. Egor Howell shares proven strategies for mastering the math needed for machine learning, including active note-taking and spaced repetition. towardsdatascience.com/how-to-learn-t…

Ready to implement Random Forests? Michael Galarnyk's tutorial provides a clear and concise guide with Python code on @GitHub for building, tuning, and interpreting Random Forest models using scikit-learn. towardsdatascience.com/understanding-…

As Derek Tran explains in a new explainer, hierarchical Bayesian modeling "enables estimation of individual-level effects by optimally combining information across different groupings of data through Bayesian updating." towardsdatascience.com/estimating-pro…

Think, Know, Act: The 3 keys to unlocking real value from AI in your enterprise. Weiwei Hu provides a practical framework for evaluating and implementing AI solutions that go beyond basic responses. towardsdatascience.com/think-know-act…

Tabular RL showdown 🥊 Oliver S put the foundational RL algorithms from Sutton & Barto to the test, comparing their speed and effectiveness in solving mazes of increasing size. towardsdatascience.com/benchmarking-t…

Marcus Sena provides a practical intro to Matplotlib's animation tools, making it easy to visualize algorithms and scientific phenomena dynamically. Read the full article free now. towardsdatascience.com/make-your-data…

80% of government data has a location — but are you processing it right? Explore how Microsoft Fabric and @ESRI GeoAnalytics tackle the challenges of big geospatial data. Great insights from Remko de Lange. towardsdatascience.com/geospatial-cap…

"Considering the trade-offs of various modeling approaches against specific objectives is essential for achieving optimal results." Kuriko Iwai walks us through the inner workings of the gradient descent algorithm. towardsdatascience.com/prototyping-gr…

PPO vs. GRPO vs. DQN, A3C, TRPO, DDPG – when to use what?? Joshua Nishanth breaks down the nuances of top RL algorithms, highlighting PPO's stability and GRPO's efficiency, with a practical #Python code example for PPO in action. towardsdatascience.com/demystifying-p…

Data science interviews test more than coding... they assess your ability to explain key statistical and ML concepts. Haden Pelletier's guide explores the fundamentals you’ll be expected to know, from how to interpret p-values to the assumptions behind linear regression and

Matrix-vector multiplication isn’t just about rules, it’s about understanding transformations. This visual-first article by Tigran Hayrapetyan introduces an “X-diagram” perspective that bridges abstract math with physical interpretation, perfect for ML practitioners building

Ingesting data from multiple sources is a common pain point. Benjamin Lee explains how Inheritance in Python can transform messy, one-off scripts into modular, maintainable, and extensible data processing pipelines. towardsdatascience.com/inheritance-a-…

Is the grass always greener in a new AI-powered IDE? Marc Matterson shares his journey with @cursor_AI and why he returned to VS @Code, especially for Project Jupyter Notebooks and cost. towardsdatascience.com/vscode-is-the-…

Build interactive data dashboards and web tools with pure Python. Learn how @Pyodide leverages #WebAssembly to run #Python libraries like #NumPy and @Matplotlib client-side from Thomas Reid. towardsdatascience.com/running-python…

.Google DeepMind's #AlphaEvolve signals a paradigm shift in AI's role in science and engineering. Luciano Abriata explores how AI can become a true partner in discovery, evolving code to reach unexpected and optimal solutions. towardsdatascience.com/googles-alphae…

Piero Paialunga simulates a restaurant pipeline, from customer arrival to order and even complaints, using individual AI agents for each role. towardsdatascience.com/hands-on-multi…