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How to Build Effective Agentic Systems with LangGraph | Towards Data Science

Towards Data Science @towardsdatascience.com · 12h

Struggling with overly complex AI integrations? Discover LangGraph to simplify your development with agentic frameworks, focusing on what matters.

By Eivind Kjosbakken

Create AI workflows with agentic frameworks

Data Visualization Explained (Part 2): An Introduction to Visual Variables | Towards Data Science

Towards Data Science @towardsdatascience.com · 18h

Feel overwhelmed by complex data visualizations? Murtaza Ali sheds light on visual encoding channels, transforming raw data into easily digestible insights through effective use of visual variables like size and color.

A non-technical and accessible guide to the underlying concept behind visual design: visual encoding channels

How to Improve the Efficiency of Your PyTorch Training Loop | Towards Data Science

Towards Data Science @towardsdatascience.com · 21h

Is your GPU starving? An inefficient data pipeline is often the hidden cause of slow model training, not the GPU itself. Andrea D’Agostino dives into the cascading bottleneck effect.

Learn how to diagnose and resolve bottlenecks in PyTorch using the num_workers, pin_memory, and profiler parameters to maximize training performance.

Data Visualization Explained: What It Is and Why It Matters | Towards Data Science

Towards Data Science @towardsdatascience.com · 23h

Murtaza Ali highlights why data visualization is a cornerstone of data science, even in an era dominated by AI and machine learning.

A brief introduction to data visualization and its importance in today's technological landscape.

Visual Pollen Classification Using CNNs and Vision Transformers | Towards Data Science

Towards Data Science @towardsdatascience.com · 1d

Discover how cutting-edge machine learning fills the data gap in pollen classification. Learn about this breakthrough dataset and models that can revolutionize ecology and biotechnology research.

By Antoni Olbrysz, Karol Struniawski, and Tomasz Wierzbicki

Filling the data gap: A machine learning approach to pollen identification in ecology and biotechnology

Prediction vs. Search Models: What Data Scientists Are Missing | Towards Data Science

Towards Data Science @towardsdatascience.com · 1d

Data scientists often focus on building precise algorithms, but there's a broader horizon to explore. Derek Tran dives into how platform firms can optimize key strategies, from partner acquisition to pricing mechanisms.

How do platform firms set prices and make money?

MobileNetV2 Paper Walkthrough: The Smarter Tiny Giant | Towards Data Science

Towards Data Science @towardsdatascience.com · 1d

Learn how to implement the MobileNetV2 architecture from scratch in PyTorch. In this new article, Muhammad Ardi explains the key concepts from the original paper, including inverted residuals and linear bottlenecks, and provides a complete, step-by-step coding guide.

Understanding and implementing MobileNetV2 with PyTorch — the next generation of MobileNetV1

PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks | Towards Data Science

Towards Data Science @towardsdatascience.com · 1d

Avishek Biswas unpacks the core mechanics of deep learning, showing how @PyTorch.org powers everything from automatic differentiation to custom neural networks.

Deep learning is shaping our world as we speak. In fact, it has been slowly revolutionizing software since the early 2010s. In 2025, PyTorch is at the forefront of this revolution, emerging as one of…

A Focused Approach to Learning SQL | Towards Data Science

Towards Data Science @towardsdatascience.com · 2d

Master SQL with a focused learning path. 🚀 This article by Mark Pedigo, thanks to @datacamp.bsky.social, teaches you to choose the right path for your career goals, helping you avoid memorization and learn with a practical project.

Data is everywhere, but how do you draw insights from it? Often, structured data is stored in relational databases, meaning collections of related tables of data. For instance, a company might store…

10 Data + AI Observations for Fall 2025 | Towards Data Science

Towards Data Science @towardsdatascience.com · 2d

Executives are championing AI, but data + AI teams in the trenches are struggling to show value.

This new article by Barr Moses explores this widening AI enthusiasm gap and argues that the solution is to empower data + AI teams to solve real business problems.

What's happening—and what's next— for data and AI at the close of 2025.

Dreaming in Blocks — MineWorld, the Minecraft World Model | Towards Data Science

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Towards Data Science @towardsdatascience.com · 2d

TDS is made by community. 🗣️ Right now we're looking for original, high-quality content that explore the evolving expectations for data scientists — especially around diverse skills like UI design, storytelling, and AI integration.

Share your article: bit.ly/TDSContributor

Towards Data Science @towardsdatascience.com · 2d

Discover the implications of the first open-source #Minecraft world model. Youssef Farag's newest article details MineWorld's architecture and its potential to accelerate research and development in fully AI-generated interactive environments.

Explaining "MineWorld: A real-time and open-source interactive world model on Minecraft" in simple terms.

Prediction vs. Search Models: What Data Scientists Are Missing | Towards Data Science

Towards Data Science @towardsdatascience.com · 2d

Data scientists often focus on building precise algorithms, but there's a broader horizon to explore. Derek Tran's article on search models reveal how platform firms can optimize key strategies, from partner acquisition to pricing mechanisms.

How do platform firms set prices and make money?

Creating and Deploying an MCP Server from Scratch | Towards Data Science

Towards Data Science @towardsdatascience.com · 2d

Vyacheslav Efimov shares a hands-on guide to building and deploying an MCP server from scratch, distilled from a Mistral hackathon challenge.

A step-by-step guide for putting an MCP server online in minutes

MCP in Practice | Towards Data Science

Towards Data Science @towardsdatascience.com · 3d

From @GitHub.com integrations to Claude Desktop, Sruly Rosenblat, Ilan Strauss, Isobel Moure, and Tim O’Reilly examine how MCP is redefining the connection between AI models, tools, and context.

Mapping power, concentration, and usage in the emerging AI developer ecosystem

Past is Prologue: How Conversational Analytics Is Changing Data Work | Towards Data Science

Towards Data Science @towardsdatascience.com · 3d

Do your reports explain *why* something is happening and what to do next? Most don't. This new article by Whitney Marks shows you how conversational analytics can provide not just an answer, but a recommended next step.

The future of reporting will be about encoding the value proposition of a product into prompt design.

How the Rise of Tabular Foundation Models Is Reshaping Data Science | Towards Data Science

Towards Data Science @towardsdatascience.com · 3d

Learn how Tabular Foundation Models (TFMs) generate predictions for new datasets without retraining. Pirmin Lemberger's new article explains this new approach, which uses in-context learning for tabular data.

A turning point for data analysis?

An easy starting point for larger and more complicated Dash dashboards

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Reposted by Towards Data Science

davidi @davidi99.bsky.social · 4d

Plotly Dash — A Structured Framework for a Multi-Page Dashboard | Towards Data Science

Use AI to Supercharge Your Learning on roadmap.sh

Reposted by Towards Data Science

roadmap.sh @roadmapsh.bsky.social · 3d

Stop struggling, start learning anything. ✅ Watch the replay where @kamrify.bsky.social, creator of Roadmap, walks you through our AI Tutor. See the full demo and learn how to get a dedicated personal tutor for any topic you choose.

In this session, I'll walk you through our AI Tutor, share the quick story of how and why we built it, then jump into the demo. You will get the chance to ask questions at the end. Come see how to…

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Towards Data Science @towardsdatascience.com · 3d

Learn how to implement the MobileNetV2 architecture from scratch in @PyTorch.org. Muhammad Ardi explains the key concepts from the original paper, including inverted residuals and linear bottlenecks, and provides a complete, step-by-step coding guide.

MobileNetV2 Paper Walkthrough: The Smarter Tiny Giant | Towards Data Science

Understanding and implementing MobileNetV2 with PyTorch — the next generation of MobileNetV1

Data Visualization Explained (Part 2): An Introduction to Visual Variables | Towards Data Science

Towards Data Science @towardsdatascience.com · 3d

Murtaza Ali breaks down the concept of visual variables. The building blocks of effective data visualization, and explains how they shape what we see and understand.

A non-technical and accessible guide to the underlying concept behind visual design: visual encoding channels

Build a Data Dashboard Using HTML, CSS, and JavaScript | Towards Data Science

Towards Data Science @towardsdatascience.com · 3d

For data scientists looking to bring their insights to life, @taupirho.bsky.social shows how to create interactive dashboards without relying on front-end frameworks.

A framework-free guide for Python programmers

Know Your Real Birthday: Astronomical Computation and Geospatial-Temporal Analytics in Python | Towards Data Science

Towards Data Science @towardsdatascience.com · 4d

Learn to solve for a precise astronomical event (the solar return ☀️) using Python. Chinmay Kakatkar's new article discusses how these methods apply to professional domains, including solar energy optimization, space mission planning, and historical event reconstruction.

A hands-on walkthrough using skyfield, timezonefinder, geopy, and pytz, and further practical applications

Eulerian Melodies: Graph Algorithms for Music Composition | Towards Data Science

Towards Data Science @towardsdatascience.com · 4d

Ever wondered how math meets music? Chinmay Kakatkar walks through using graph theory to generate melodies with Python in a fascinating blend of art and algorithms.

Conceptual overview and an end-to-end Python implementation