
Pierre DeBois
Founder and CEO, Zimana and Contributor at CMSWire
#analytics #marketing #datascience #rstats services #smallbiz contributor @InformationWeek @ITProToday @CMSWire @smallbiztrends #BlackLivesMatter #BlackInData
Articles
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2 days ago |
zimanaanalytics.medium.com | Pierre DeBois
When I last explained about LMStudio, the hosting platform for local AI development, I noted how developers can create AI models using smaller LLMs, called small language models. Many of the LMStudio display model size parameters, which you use to select a model.
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2 days ago |
cmswire.com | Pierre DeBois
Explore the new rules of AI search and how marketers can stay visible in an evolving SERP landscape. AI has changed the rules of SEO. Traditional keyword-based approaches must evolve to match AI’s prioritization of context, quality, and user intent. Enter AISO: AI Search Optimization. Marketers must optimize for how AI summarizes and ranks content across evolving SERPs and conversational experiences. New playbook required.
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1 week ago |
cmswire.com | Pierre DeBois
Unify touchpoints, deploy predictive models and create insight-to-action loops that actually scale. Personalization through AI. Artificial intelligence helps marketers connect fragmented touchpoints into coherent journeys. Faster insight-to-action. AI reduces the time it takes to go from raw data to real-time decision-making. New visibility into journeys. AI-driven pattern recognition and prediction replace outdated dashboards.
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2 weeks ago |
cmswire.com | Pierre DeBois
It’s time to move beyond vanity metrics. Discover how AI turns customer data into performance-ready action. AI-powered insights. AI-driven predictive analytics allows marketers to forecast future customer behaviors and trends with greater accuracy. Real-time adaptability. By using real-time data and AI, businesses can make faster, more informed decisions that directly improve CX and drive KPIs. AI for data storytelling.
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3 weeks ago |
zimanaanalytics.medium.com | Pierre DeBois
Data — be it in R, SQL, or Python — are always categorized. Understanding binning and slicing can lead to better choices for planning data models. Here’s how. Pierre DeBois·Follow5 min read·--The world is awash in data, and many times we have to categorize that data before it is applied to a data model to perform an advanced calculation. The starting point for a good categorization strategy is to identify what data should be binned and what data should be sliced.
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RT @DMBeat: What Makes NotebookLM Appealing for Marketers? by @zimanaanalytics https://t.co/WtkVoU5t4v

RT @CXMWorld: What Makes NotebookLM Appealing for Marketers? by @zimanaanalytics https://t.co/7495LaV5hn

RT @CXMWorld: Will ChatGPT Search Change Everything in SEO? by @zimanaanalytics https://t.co/zC7oOr7FxK