Takeaways on how to run ML projects on Azure from a Microsoft engineer – author of the Azure Data Scientist Associate Certification Guide.
Category: AI
AI (Artificial Intelligence) are machines acting in ways that seem intelligent. Our goal in technology should be connecting people and computers so that – collectively – they act more intelligently than any person or group of machines. I.e., AI should boost organizations to make them more intelligent.
Artificial Intelligence is a difficult capability to master. It requires to have enough high-quality data. Additionally, its development and maintenance require catering to data life cycle and software.
Moreover, how the algorithms work evolves based on how they adapt to the data they receive. The results are difficult to predict, and they often pass inadvertently.
For me, there is also an additional source of concern. Data and Artificial Intelligence are of paramount importance to make informed decisions, predict outcomes and, overall, create more intelligent organizations. However, many governments, organizations and citizens don’t know what it is, how to use it and its impact. They dread the consequences on citizens’ privacy, estates’ security and the work market. While at the same time, they neglect or are unaware of some effects.
I will explore in this blog what AI is: use cases, pros and cons, pitfalls, solutions to implement it and examples. I will also share cookbooks and demos. My ultimate goal is to demystify AI. I want to explain why it is beneficial and how it solves some current issues. I also want to make everyone more confident about some possible outcomes. Finally, I will explain how some perceived threads are not such and hidden dangers most people are unaware of.
Andreas Botsikas – Microsoft engineer, author of the Azure Data Scientist Guide
“ML models are in fashion, such as customer churn predictions. However, it’s not easy to define what a churned customer is unless you have a multi subscription system like Netflix, where you can quickly identify the customers who stopped paying. E.g., what does churn mean for a supermarket?”
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