Data Science
Data Science | News, how-tos, features, reviews, and videos
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.
What is generative AI? The evolution of artificial intelligence
Artificial intelligence is already designing microchips and sending us spam, so what's next? Here's how generative AI really works and what to expect now that it's here.
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.
Embrace and extend Excel for AI data prep
Combining machine learning and Excel can get you the data transformation you need while data scientists are scarce.
nbdev v2 review: Git-friendly Jupyter Notebooks
Add-on to Jupyter Notebooks enables a literate Python development style that gives you high-quality documentation, tests, continuous integration, and packaging for free.
The tip of the data science iceberg
Data science is already a vital element of a successful business. Before long it will be part of every application, and AI will be embedded in every transaction workflow.
Why Python is catching on with business analysts
Business analysts are running into the limits of BI tools and looking for ways to do more advanced analytics. Python is the way forward.
Cloud computing gets back to basics
Recent trends show a return to cloud fundamentals, such as data, development, deployment, and security, rather than chasing what’s new and cool.
5 risks of AI and machine learning that modelops remediates
Modelops improves machine learning model development, testing, deployment, and monitoring. Follow these tips to keep model risks in check and increase the efficiency and usefulness of your ML initiatives.
Data lake upstart Upsolver takes aim at Databricks
The San Francisco-based startup has released a SQL-based, self-orchestrating data pipeline platform, claiming it will go to go toe-to-toe with Databricks’ Delta Live Tables.
Book review: 'Python Tools for Scientists'
Python has a wealth of scientific computing tools, so how do you decide which ones are right for you? This book cuts through the noise to help you deliver results.
5 modelops capabilities that boost data science productivity
Organizations are hiring data scientists to develop ML models and experiment with AI, but the business impact is lagging for many large enterprises.
A beginner's guide to using Observable JavaScript, R, and Python with Quarto
Using Quarto with Observable JavaScript is a great solution for R and Python users who want to create more interactive and visually engaging reports.
Data visualization with Observable JavaScript
Learn how to make the most of Observable JavaScript and the Observable Plot library, including a step-by-step guide to eight basic data visualization tasks in Plot.
Learn Observable JavaScript with Observable notebooks
Free, hosted Observable notebooks provide an interactive experience and lots of free, open-source Observable JS code you can reuse and learn from. Here's how to get started.
How to choose a cloud machine learning platform
12 capabilities every cloud machine learning platform should provide to support the complete machine learning lifecycle—and which cloud machine learning platforms provide them.
The importance of monitoring machine learning models
Changing assumptions and ever-changing data mean the work doesn’t end after deploying machine learning models to production. These best practices keep complex models reliable.
