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If you want to squeeze the most value from your data, teach your employees Python and Excel instead of specialized programming languages.
Microsoft’s Azure Space platform and Azure Orbital Space SDK are taking edge computing to the final frontier, starting with satellite image processing, geospatial, and communications applications.
Microsoft Azure’s new, unified data platform aims to be your one-stop shop for analytics and machine learning at scale.
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?
When the goal is accuracy, consistency, mastering a game, or finding the one right answer, reinforcement learning models beat generative AI.
Data debt can be just as bad as tech debt, causing security and trust problems if it isn’t addressed throughout the data pipeline.
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.
Combining machine learning and Excel can get you the data transformation you need while data scientists are scarce.
Because building reliable data pipelines is hard, and the first step to becoming a data-driven organization is trusting your data.
Think of artificial intelligence as a useful tool to help a company take small steps forward, rather than something to supplant people.
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