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Choosing the Right Prompt for Language Models: A Key to Task-Specific Performance
Imagine conversing with a language model that understands your needs, responds appropriately, and provides valuable insights. This level of interaction…
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Recommender System Optimization for Online Platforms: A Comparative Study Using Comet
Photo by C D-X on Unsplash Imagine scrolling through your favorite online platform, whether it’s Netflix, YouTube, or Spotify, searching…
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LLMs: Exploring Data with YOLOPandas š¼ and Comet
Have you ever imagined how cool it would be to analyze, explore and visualize your data in Pandas without typing…
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Plan-and-Execute Agents in Langchain
Evolution from Action to Plan-and-Execute Traditional āAction Agentsā followed a framework where user input was received, the agent decided on…
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Using the ReAct Framework in LangChain
Both ways: Using off-the-shelf agents and LCEL ReAct Framework for Prompting ReAct, which stands for Reasoning + Acting, is a prompting…
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Conversational Agents in LangChain
Both ways: off-the-shelf and using LCEL Conversational Agents Conversational agents in LangChain facilitate interactive and dynamic conversations with users. Conversation agents…
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Evaluation Metrics for Classification Models in Machine Learning (Part 2)
Photo by Jon Tyson on Unsplash In machine learning, data scientists use evaluation metrics to assess the model’s performance in…
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Evaluation Metrics for Classification Models in Machine Learning (Part 1)
Photo by Jon Tyson on Unsplash Suppose you are working on a machine learning classification problem in which you have…
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Image Captioning Model with TensorFlow, Transformers, and Kangas for Image Visualization
Image captioning is a compelling field that connects computer vision and natural language processing, enabling machines to generate textual descriptions…
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Data Fabric & Data Mesh: Two Approaches, One Data-Driven Destiny
I decided to write a series of blogs on current topics: the elements of data governance that I have been…