How AI has massively changed my day-to-day workflow

The post A Day in the Life of a Data Scientist in 2026 appeared first on Towards Data Science.

A preprocessing pipeline let my car price model peek at the test set before the exam, and the twelve points of R squared it cheated its way to

The post My Model Was Cheating on Its Own Test appeared first on Towards Data Science.

A practical guide to choose the proper tool for your agentic workflows and systems

The post LangChain vs LangGraph: 4 Key Differences and When to Use Each appeared first on Towards Data Science.

From one gradient to every gradient

The post Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works appeared first on Towards Data Science.

A reproducible Lagos case study with population data, transport access, and airspace constraints

The post How to Place Vertiport Locations in Any City Using Geospatial Machine Learning appeared first on Towards Data Science.

Not all Python data libraries are created equal!

The post Should AI Developers Make the Switch from Polars to Pandas? appeared first on Towards Data Science.

How to diversify a budget without losing the shadow prices that explain the result

The post The Budget Split That Explains Itself appeared first on Towards Data Science.

Building my first dbt models and learning what “analysis-ready” data actually means

The post I Thought Loading Data Was the Finish Line. It Was the Starting Point. appeared first on Towards Data Science.

From Static Plots to Interactive Data Exploration

The post Matplotlib vs Plotly: Which Python Chart Tool Should You Choose? appeared first on Towards Data Science.

Faster dataframe engines are nice, but they don't reduce the amount of syntax an analyst has to hold in their head.

The post The Problem with pandas Isn’t Performance. It’s Cognitive Overhead. appeared first on Towards Data Science.

The downside of conference travel

The post Last Month’s Machine Learning Lessons Learned appeared first on Towards Data Science.

A primer about Semi-Supervised Learning, the approaches taken with different algorithms and the limitations of using unlabelled data.

The post Introduction to Semi-Supervised Learning appeared first on Towards Data Science.

An online simulation and a novel method for increasing power

The post How to Get More Statistical Power from Fewer Research Participants appeared first on Towards Data Science.

Data Storytelling Series, Chapter 1

The post Are Home Teams Favoured by Referees in Football/Soccer? appeared first on Towards Data Science.

NVIDIA nvmath-python is a library designed to bridge the gap between the Python scientific community and NVIDIA CUDA-X math libraries. It gives Python users...

NVIDIA nvmath-python is a library designed to bridge the gap between the Python scientific community and NVIDIA CUDA-X math libraries. It gives Python users access to CUDA-X performance for common math operations without disrupting existing workflows. Depending on the API, operations can run on a CPU, CUDA-enabled GPU, or distributed multi-GPU, multi-node systems.

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NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they...

NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they should be tuned to continue operating. This post introduces the latest model release, NVIDIA Ising Calibration 1.5, which advances AI-based QPU calibration by analyzing unfamiliar diagnostic results without prior training examples.

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Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings...

Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings and stock movements, while rarer events such as credit-rating changes, product approvals, and labor issues are harder to capture at scale. Synthetic generation can help fill those gaps for trading research, risk modeling, and surveillance…

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Presto is an open source, distributed SQL engine for running fast, interactive queries on very large datasets. On NVIDIA GPUs, Presto delivers peak performance...

Presto is an open source, distributed SQL engine for running fast, interactive queries on very large datasets. On NVIDIA GPUs, Presto delivers peak performance for analytical query workloads and provides low latency for users and agents. GPU-accelerated Presto brings low latency to your analytical workloads, keeping you and your agents unblocked and iterating as fast as possible.

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GPU-accelerated query engines are often constrained by memory and I/O bandwidth. NVIDIA hardware advances—including high bandwidth memory (HBM), NVIDIA...

GPU-accelerated query engines are often constrained by memory and I/O bandwidth. NVIDIA hardware advances—including high bandwidth memory (HBM), NVIDIA NVLink-C2C, and dedicated decompression engines featured in NVIDIA GB200 NVL4—help remove these bottlenecks by increasing effective storage capacity, accelerating data movement between CPUs and GPUs, and speeding data access without consuming…

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AI scientists are emerging as a new interface for scientific computing. These agents can read papers, write code, generate hypotheses, call APIs, inspect files,...

AI scientists are emerging as a new interface for scientific computing. These agents can read papers, write code, generate hypotheses, call APIs, inspect files, and iterate on results. But science isn’t software engineering. There is no test suite that turns green when a hypothesis is correct; discovery is iterative, uncertain, and grounded in the physical world. You can’t take a general coding…

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