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Using Graphs for Feature Engineering, Prompt Fine-Tuning for Generative AI, and Confident Data…

ODSC - Open Data Science

How to Land a Job After a Data Science Bootcamp You just finished your data science bootcamp, what’s next? Follow these steps to successfully start your job search afterward! However, unlocking its potential in enterprise environments requires addressing critical concerns related to accuracy, privacy, and legality.

AI 98
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How to build a successful talent acquisition strategy

IBM Journey to AI blog

Develop candidate profiles: Create personas for ideal candidates and write detailed job descriptions for each role based on the skills and qualifications necessary for success. Job boards: Post openings on popular job boards and career websites such as Indeed, LinkedIn, Glassdoor and Monster to reach active job seekers.

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What Can AI Teach Us About Data Centers?

ODSC - Open Data Science

While questions about these topics complete my three-part series with ChatGPT about data centers, keep in mind that recommendations for how to use ChatGPT and other large language model (LLM)-based chatbots continue to evolve. He offers several principles for “prompting” or “prompt engineering” and covers the basics of this topic.

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Deploying Conversational AI Products to Production With Jason Flaks

The MLOps Blog

Every episode is focused on one specific ML topic, and during this one, we talked to Jason Falks about deploying conversational AI products to production. That was kind of my out-of-the-gate job. And on the topic of equipment, you were involved in developing the Connect, right? (Or Jason: Yeah, that’s right. Or the Xbox).

AI 52
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3 Tips from Deloitte on Leading a Data Viz Competition at Work

Tableau

Objective: Deriving insights from raw data around the topic of diversity, equity and inclusion. The Deloitte participants put in remarkable effort on top of demanding day jobs. This year it was fun to explore stunning insights in the field of DE&I, a truly important topic with respect to our connected world.”

Tableau 86
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3 Tips from Deloitte on Leading a Data Viz Competition at Work

Tableau

Objective: Deriving insights from raw data around the topic of diversity, equity and inclusion. The Deloitte participants put in remarkable effort on top of demanding day jobs. This year it was fun to explore stunning insights in the field of DE&I, a truly important topic with respect to our connected world.”

Tableau 78
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3 Tips from Deloitte on Leading a Data Viz Competition at Work

Tableau

Objective: Deriving insights from raw data around the topic of diversity, equity and inclusion. The Deloitte participants put in remarkable effort on top of demanding day jobs. This year it was fun to explore stunning insights in the field of DE&I, a truly important topic with respect to our connected world.”

Tableau 52