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LLMs - Practical Applications

LLMs - Practical Applications 1. Talk to your PDF (Github) - ask questions/answers from the content in your PDF file. Talk to your PDF 2. Product Description Generation Prompt (Github) - generate product description from the Technical Specifications. Product Description Generation Prompt 3. Summarize Product Reviews (Github) - Summarize multiple Customer reviews on the products. Summarize Product Reviews 4. Sentiment Analysis LLM Sentiment Analysis LLM 5. Language Translation and More: Translate languages, Tone, Spell/Grammar checks,  Language Translation and More 6. Customized Automatic Email for Positive or Negative feedback Customized Automatic Emails 7. LLM on Housing Data using Agentic RAG  AgenticRAG More to follow...
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Prompt Engineering: Personalized Prompts

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Prompt Engineering: My Personalized Prompts    Here's my Personalized Prompts developed on ChatGPT 3.5: 1. Product Description Summarizer - summarize the product description for an E-commerce retailer.  Product Description Summarizer 2. Competitor Analysis Report Builder - just add your company product offerings and list a few competitors and get a Competitor Analysis report   Competitor Analysis Report Builder More to follow... Also see:  Chatbot Product Recommendations
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Chatbot Product Recommendations using NLP

 Chatbot Product Recommendations using NLP Business Objective: Provide instant assistance to customers on product recommendations on a Customer Service Chatbot at eCommerce business Tip: Try it in Google Colab! 1. Generate Dataset import pandas as pd # Create a synthetic dataset for customer queries and interactions data = {     'query' : [ 'How can I track my order?' , 'Do you have this item in stock?' , 'Can I return this product?' ,               'Which products are trending?' , 'Can you recommend a laptop for programming?' ],     'intent' : [ 'order_tracking' , 'product_availability' , 'return_policy' ,                 'trending_products' , 'product_recommendation' ],     'response' : [ 'To track your order, please visit our website and go to the order tracking section.' ,                   'Yes, the item is currently in stock.' ,                   'Our retu
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AI Strategy for Digital Business High-level framework to define AI Strategy. 1.     Define Business Goals: •        Identify Digital business overarching business objectives. •        Understand key performance indicators (KPIs) and success metrics. •        Determine how AI can contribute to achieving these goals. 2. Understand Client Needs: •        Conduct client surveys, interviews, and feedback sessions via Mural boards. •        Identify common pain points and challenges faced by clients. •        Determine where AI can enhance client satisfaction and deliver value. 3. Assess Current Capabilities: •        Evaluate existing AI capabilities within Apply Digital. •        Identify areas where AI can be integrated or improved. •        Assess the skillset of the current workforce in relation to AI. 4. Establish Clear AI Objectives: •        Define specific, measurable, achievable, relevant, and time-bound (SMART) AI objectives. •        Align AI goals wit
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Developing an effective AI strategy for Retail and E-commerce business

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Role-based AI Strategy for E-commerce and Retail Developing an effective AI strategy for a mid-size Retail and E-commerce business involves aligning AI initiatives with business goals, enhancing customer experiences, and optimizing operations. Let’s break down the roles and their corresponding AI strategies: Also see: Chatbot Product Recommendations  https://digitalecomai.blogspot.com/2024/02/chatbot-product-recommendations-using.html
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