Science Score: 44.0%
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Low similarity (16.0%) to scientific vocabulary
Repository
Notes from https://github.com/bahree/GenAIBook
Basic Info
- Host: GitHub
- Owner: ysantosh
- License: mit
- Language: Python
- Default Branch: main
- Size: 23.8 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Book - Generative AI in Action
Forked from - https://github.com/bahree/GenAIBook/ . This is for self learning while reading book Generative AI in Action and for personal consumption only. This repo might have some changes which doesn't work at all. Please use original author repo. Welcome to the code repo associated with my book Generative AI in Action, published by Manning.
Note: The book is also available on Amazon.

This repo has a few things that might be of interest: * Code from the different examples in the book. * List of research papers associated with different AI technology and techniques. * A Web application you can run locally brings many of these concepts together. * Detailed instructions for getting dependencies installed locally.
| :warning: Warning: OpenAI API Breaking Changes |
| --- |
The book's code works with the new API (v1.0) that OpenAI recently updated. If you have an old package version (v0.28), upgrade to the latest version for the code to work. To upgrade the package, you can run the following command: pip install --upgrade openai. If you are using conda, you can run the command: conda update openai.
Core dependencies :minidisc:
Before we start installation instructions, as outlined in the book, we assume you have installed the following basic dependencies. For most developers and data scientists, these would already be in place, and there might not be any additional steps needed.
Note: If any of these are missing and need step-by-step instructions, see detailed dependency installation instructions.
* IDE: Visual Studio Code (or similar) 💻.
* Python: Version 3.7.1 or later; we use version 3.11.3 for the book.
* To check the Python version installed, run: python --version
* Package manager: Although technically a package manager is not needed, it would make things much easier to maintain. We use conda for the book, but you can use any you prefer.
* Git: Given we are using GitHub, you need Git installed locally.
Installation instructions :books:
The steps to get the environment up and running can be found in the installation instructions.
Where is the Code? :file_folder:
The book's code is organized by chapters as expected and is in the folder called chapters. You will find a folder for each chapter following the convention of ch{chapter-number}.
You can find some utility functions and programs in the utils folder.
Web Application :earth_americas:
In addition to the code from the chapter, a fully functional web application brings all the different constructs together in an easy-to-navigate web application that you can run locally. The code for this can be found in the webapp folder. :panda_face:
Note: :information_source: The web application is meant only as a reference to run locally and not exposed to the internet. It does not have all the necessary proxies and controls one would build when exposing an application to the internet.
Papers :pagefacingup:
LLM and Generative AI are still quite new, and as a result, there is a fascinating list of very active research. You can find a pointer to many of these in the paper folder . These are organized by Chapter to help you navigate.
The reader is not expected to know these but as with most things, it is always good to go deeper and grok some of these concepts for a better and fuller understanding.
Contact
You can see my GitHub profile for different ways to get in touch. If there are any questions, or issues, please submit an Issue.
License
The work as part of this repo is shared under MIT License. In summary, this is a short and simple permissive license with conditions only requiring the preservation of copyright and license notices. Licensed, modified, and larger works may be distributed under different terms and without source code.
Owner
- Name: Santosh Yadav
- Login: ysantosh
- Kind: user
- Repositories: 11
- Profile: https://github.com/ysantosh
Citation (CITATION.cff)
# cff-version: 1.2.0
# message: "If you use this book or any of the work, I would appreciate if you can cite it as below."
# authors:
# - family-names: "Bahree"
# given-names: "Amit"
# orcid: "https://orcid.org/0009-0000-9596-8652"
# title: "Generative AI in Action"
# version: 2.0.4
# date-released: 2024-07-11
# url: "https://github.com/bahree/GenAIBook"
# preferred-citation:
# type: book
# authors:
# - family-names: "Bahree"
# given-names: "Amit"
# orcid: "https://orcid.org/0009-0000-9596-8652"
# title: "Generative AI in Action"
# year: 2017
# publisher:
# name: Manning
# medium: print
cff-version: 1.2.0
title: Generative AI in Action
message: >-
If you use this book or any of the work, I would
appreciate it if you can cite it as below.
type: book
authors:
- family-names: Bahree
given-names: Amit
orcid: 'https://orcid.org/0009-0000-9596-8652'
repository-code: 'https://github.com/bahree/GenAIBook'
url: 'https://github.com/bahree/GenAIBook'
abstract: >-
Generative AI has created new opportunities for
organizations of all sizes. You can easily use tools like
ChatGPT, Bard, and Stable Diffusion to generate text and
images for product catalogs, marketing campaigns,
technical reporting, and other common tasks. Coding
assistants like Copilot are accelerating productivity in
software teams. In this insightful book, author Amit
Bahree shares his experience leading Generative AI
projects at Microsoft for nearly a decade, starting well
before the current GPT revolution.
keywords:
- LLM
- SLM
- GenAI
- AI
- GPT
license: MIT
version: '1.0'
date-released: '2024-07-01'
preferred-citation:
type: book
authors:
- family-names: "Bahree"
given-names: "Amit"
orcid: "https://orcid.org/0009-0000-9596-8652"
title: "Generative AI in Action"
year: 2024
publisher:
name: Manning
medium: print
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