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10 most difficult-to-fill IT roles β€” and how to address the gap

CIO

But, notes Lobo, β€œin all geographies, finding well-rounded leadership and experienced technical talent in areas such as legacy technologies, cybersecurity, and data science remains a challenge.” CIOs must up their talent game across the board, including talent management, engagement, training, and retention, in addition to hiring.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning - AI

What operational and technical best practices can I integrate into how my organization builds generative AI LLM applications to manage risk and increase confidence in generative AI applications using LLMs? What are some ways to implement security and privacy controls in the development lifecycle for generative AI LLM applications on AWS?

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Top Data Science experts you should know about

Apiumhub

He also writes compelling articles about Big Data and related topics for publications such as Data Science Central, DataFloq and Dataconomy. He is an advisory board member for the Big Data training category at Simplilearn and an online education provider. Kirk Borne is a Principal Data Scientist at Booz Allen Hamilton.

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How to Hire AI Developers?

Existek

Besides, their responsibilities include considering such factors as data type, volume, complexity, etc. Training and optimization: They use data to build and train AI models. Using prepared data, AI software developers can implement techniques to evaluate and optimize model performance.

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Technology Trends for 2024

O'Reilly Media - Ideas

Use of content about event-driven architecture is relatively small, but it’s up 40%. That change is important because event-driven architecture is a tool for designing large systems that have to ingest data from many different streams in real time. So what does all this tell us about training and skill development?

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

Altexsoft

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?