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Developing Kaggle Notebooks

You're reading from   Developing Kaggle Notebooks Pave your way to becoming a Kaggle Notebooks Grandmaster

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781805128519
Length 370 pages
Edition 1st Edition
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Author (1):
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Gabriel Preda Gabriel Preda
Author Profile Icon Gabriel Preda
Gabriel Preda
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Table of Contents (14) Chapters Close

Preface 1. Introducing Kaggle and Its Basic Functions FREE CHAPTER 2. Getting Ready for Your Kaggle Environment 3. Starting Our Travel – Surviving the Titanic Disaster 4. Take a Break and Have a Beer or Coffee in London 5. Get Back to Work and Optimize Microloans for Developing Countries 6. Can You Predict Bee Subspecies? 7. Text Analysis Is All You Need 8. Analyzing Acoustic Signals to Predict the Next Simulated Earthquake 9. Can You Find Out Which Movie Is a Deepfake? 10. Unleash the Power of Generative AI with Kaggle Models 11. Closing Our Journey: How to Stay Relevant and on Top 12. Other Books You May Enjoy
13. Index

Building a multi-task application with Langchain

Langchain is the most popular task-chaining framework (Reference 8). Task chaining is an extension of the prompt engineering concept that we illustrated in the previous section. Chains serve as predetermined sequences of operations, designed to organize intricate processes in a format that is both more manageable and easier to understand. These chains follow a distinct order of actions. They are well suited for workflows characterized by a consistent number of steps. With task chaining, you can create sequences of prompts, where the output of the previous task executed by the framework is fed as input for the next task.

Besides Langchain, there are now several other options available for task chaining, like LlamaIndex or Semantic Kernel (from Microsoft). Langchain provides multiple functionalities, including specialized tools to ingest data or output results, intelligent agents, as well as the possibility to extend it by defining...

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