Forecasting and Making Predictions with GenAI / LLMs in #MicrosoftFabric using #langchain #OpenAI

AI Data Scientist Expert

The use of LLMs for real-time data predictions represents a significant leap in data science, particularly in operational settings. By leveraging prompt engineering, the approach showcased allows for a nuanced understanding of trends within customer interactions, redefining traditional predictive modeling. Future applications could include dynamic recommendation systems in e-commerce, where businesses can better tailor their services based on customer behavior analytics.

AI Business Strategy Expert

Employing generative AI like GPT-4 in predictive analytics suggests a shift toward data-driven decision-making across industries. This technique facilitates not only improved accuracy in predictions but also enhances responsiveness to market trends. Businesses can capitalize on this by integrating such AI capabilities into their decision frameworks, leading to more agile strategies that directly enhance customer experience and operational efficiency.

Forecasting

In this video, forecasting is performed using LLMs to predict tip amounts.

Generative AI

The video illustrates generative AI's application in predicting restaurant tip percentages.

Large Language Models (LLMs)

The presenter utilizes LLMs for data-driven predictions without traditional machine learning.

OpenAI

This AI model is employed in the video for making reliable predictions and forecasts.

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Microsoft

The video discusses the potential of Microsoft's tools combined with LLMs for operational logic.

Mentions: 2