Introduction to Large Language Models (LLMs) In Python

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Introduction to Large Language Models (LLMs) In Python (Size: 1.3 GB)
  1. Introduction to Numpy.mp4 29.9 MB
  1. Overview-The Summarisation Process.mp4 34.9 MB
  1. Read in a Single PDF.mp4 17.2 MB
  1. Welcome To the Course.mp4 30.3 MB
  1. What Is Prompt Engineering.mp4 40 MB
  1. What Is a Document Reading Virtual Assistant.mp4 21.1 MB
  2. Abstract Summarizer.mp4 62.3 MB
  2. Data and Code.html 409.6 B
  2. Get Access To the OpenAI API.mp4 18.6 MB
  2. Prompt Engineering With Langchain.mp4 64.2 MB
  2. Read In Multiple PDFs.mp4 71.2 MB
  2. What Is Pandas.mp4 74.9 MB
  3. A More Straightforward Way To Read in Multiple PDFs.mp4 37.1 MB
  3. Answer Questions Based On Given Text-LangChain.mp4 69.9 MB
  3. Basic Data Cleaning With Pandas.mp4 34.4 MB
  3. Introduction to LangChain.mp4 36.7 MB
  3. Python Installation.mp4 42.6 MB
  4. Basic Principles of Data Visualisation.mp4 73.9 MB
  4. Learn More About Your Documents Why We Need A Preliminary NLP Analysis.mp4 19 MB
  4. Start With Google Colaboratory Environment.mp4 40.4 MB
  4. Theoretical Undepinnings.mp4 25 MB
  5. Answer Questions With Llama-Index.mp4 35.6 MB
  5. Entity Matching.mp4 90.8 MB
  5. Google Colabs and GPU.mp4 30.2 MB
  6. Installing Packages In Google Colab.mp4 28.6 MB
  6. Keyword Extraction.mp4 79.8 MB
  7. Another Cloud To Work In Saturn Cloud.mp4 48.3 MB
  7. What Is TF-IDF.mp4 22.9 MB
  8. Say Hello To The Saturn Interface.mp4 30.3 MB
  8. Text Similarity.mp4 74.1 MB
  9. Brain Fail Dealing With Memory Problems.mp4 14.9 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 33 total files

Description


Introduction to Large Language Models (LLMs) In Python
https://FreeCourseWeb.com

Published 9/2023
Created by Minerva Singh
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 31 Lectures ( 2h 45m ) | Size: 1.3 GB

Develop Your Own Document-Reading Virtual Assistant With LLMs

What you'll learn
Learn to work with Jupyter notebooks in a brand new cloud ecosystem-Saturn Cloud
Read in multiple PDFs into Python
Implement common natural language processing (NLP) techniques including entity recognition and keyword extraction
Get acquainted with common Large Language Model (LLM) frameworks including LangChain
Implement LLM frameworks for abstract summarisation and answering questions

Requirements
Prior experience of using Jupyter notebooks
Prior exposure to Natural Language Processing (NLP) concepts will be helpful but not compulsory
An interest in using Large Language Models (LLMs) for your own documents

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