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Python Pandas creator Wes McKinney joins Posit

Python pandas creator Wes McKinney has joined data science company Posit as a principal architect, signaling the company's efforts to play a bigger role in the Python universe as well as the R ecosystem.

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BI meets data science in Microsoft Fabric

Microsoft’s cloud-hosted data lake and lakehouse platform gains new data science tools and opens up Power BI datasets to Python, R, and SparkSQL.

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Review: 7 Python IDEs compared

What's the best IDE for Python? Here's how IDLE, Komodo, PyCharm, PyDev, Microsoft's Python and Python Tools extensions for Visual Studio Code, and Spyder stack up.

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People and Python in AI

If you want to squeeze the most value from your data, teach your employees Python and Excel instead of specialized programming languages.

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How to take action against AI bias

Humans must be the custodians for preserving high-quality data as AI use continues to advance.

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What is generative AI? Artificial intelligence that creates

Generative AI models can carry on conversations, answer questions, write stories, produce source code, and create images and videos of almost any description. Here's how generative AI works, how it's being used, and why it’s more...

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Splunk’s new AI tools aim to ease security, observability tasks

The AI tools introduced at the company’s .conf2023 include the Splunk AI Assistant, Splunk Machine Learning Toolkit 5.4, Splunk App for Anomaly Detection, and the Splunk App for Data Science and Deep Learning 5.1.

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The engines of AI: Machine learning algorithms explained

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

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Coding with AI: Tips and best practices from developers

AI pair programming could be a coder's dream or a nightmare in the making. Nine developers talk shop about how they're using generative AI today. 


ChatGPT’s parasitic machine

What do ChatGPT and other large language models owe to the human creators who provide the information they train on? What if creators stop making their insights publicly available?

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5 best practices for software development partnerships

Partnerships can accelerate technological innovation in agile, devops, and data science. Just make sure you start with a strong foundation in place.

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5 newer data science tools you should be using with Python

Already using NumPy, Pandas, and scikit-learn? Here are five more powerful Python data science tools ready for a place in your toolkit.

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14 popular AI algorithms and their uses

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases.

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Preview: Google Cloud Dataplex wows

Google Cloud Dataplex is an amazingly complete system for turning raw data from silos into unified data products ready for analysis. And a bit overwhelming to learn.

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6 ways to avoid and reduce data debt

Data debt can be just as bad as tech debt, causing security and trust problems if it isn’t addressed throughout the data pipeline.

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How to babysit your AI

AI systems are not yet mature and capable enough to operate independently, but they can still work wonders with human help. We just need a few guardrails.

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How to explain the machine learning life cycle to business execs

For data science teams to succeed, business leaders need to understand the importance of MLops, modelops, and the machine learning life cycle. Try these analogies and examples to cut through the jargon.

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Data Workshops for Ukraine: Learn a skill and support a cause

The two-hour workshops offer training in data visualization and analysis with R, Python, and SQL and cost just $20 or €20. Next up is ChatGPT in R.

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