LangChain MasterClass- #8 OpenAI LLM & Pinecone Python Apps

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size2.5 GB
  • Uploaded Bytutsnode
  • Downloads81
  • Last checkedJul. 18th '23
  • Date uploadedJul. 18th '23
  • Seeders 38
  • Leechers30
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Infohash : 60E4D431281714CE6AC0E50126D5C88F92049435


Description

Unlock the Power of AI with LangChain: Learn to Create Revolutionary Language-Based Applications

Looking to harness the full potential of AI and revolutionize the world of language-based applications? Look no further than LangChain, the comprehensive course designed to transform you from a novice to an expert in record time.

Embark on an exciting journey of project-based learning, where you will implement cutting-edge AI applications powered by state-of-the-art LLM models like OpenAI and Hugging Face, using the versatile Python programming language.

With LangChain, you will acquire the skills and knowledge necessary to develop innovative LLM solutions for a wide range of real-world problems. Dive into hands-on projects that will shape your expertise, including:

Project 1: Construct a dynamic question-answering application with the unparalleled capabilities of LangChain, OpenAI, and Hugging Face Spaces.

Project 2: Develop an engaging conversational bot using LangChain and OpenAI to deliver an interactive user experience.

Project 3: Create an AI-powered app tailored for children, facilitating the discovery of related classes of objects and fostering educational growth.

Project 4: Build a captivating marketing campaign app that utilizes the persuasive potential of well-crafted sales copy, boosting sales and brand reach.

Project 5: Develop a ChatGPT clone with an added summarization feature, delivering a versatile and invaluable chatbot experience.

Project 6: MCQ Quiz Creator App – Seamlessly create multiple-choice quizzes for your students using LangChain and Pinecone.

Project 7: CSV Data Analysis Toll – Helps you analyze your CSV file by answering your queries about its data.

Project 8: Youtube Script Writing Tool – Effortlessly create compelling YouTube scripts with this user-friendly and efficient script-writing tool.

LangChain empowers programmers to harness the full potential of large language models like ChatGPT and Pinecone, enabling seamless integration with external data sources. This integration enhances the models’ ability to comprehend and respond to human language, opening up a world of possibilities.

Tailored specifically for beginners, LangChain’s user-friendly interface, built with Python, ensures accessibility for aspiring developers and enthusiasts alike. Leave behind basic techniques like keyword matching and rule-based systems, and elevate your capabilities with LangChain.

Course Highlights:

Unlock the true potential of LangChain, LLMs, Chat Models, Prompts, Indexes, Data Connections, Chains, Agents, and Memory.
Harness the power of LLMs and LangChain to develop robust applications, integrating cognitive and information sources with Pinecone.
Explore new horizons and unleash unprecedented possibilities with LangChain and Pinecone-powered applications.

The LangChain course isn’t just theory-based; it’s a hands-on, transformative experience. Engage in practical activities and real-world projects that will solidify your understanding of these concepts and techniques.

By the end of the course, you will possess the skills and expertise to effectively apply LangChain, building powerful, scalable, and efficient LLM applications for diverse purposes.

Don’t miss this incredible opportunity to become a language model expert. Enroll in the LangChain course today and embark on a transformative journey that will elevate your AI app development skills. LangChain, OpenAI, ChatGPT, LLM, Python, and Pinecone are the tools that will empower you to create cutting-edge AI applications that push the boundaries of what’s possible.

Unlock your full potential and become a hero in the world of language-based AI development through LangChain and Pinecone.

Join now and start building the future of AI applications with LangChain and Pinecone!
Who this course is for:

Anyone who is excited to buil;d AI powered LLM apps using Langchain
Someone who is planning to start his a career as an LangChiain Professional and would like to explore the tool.
AI Enthusiast

Requirements

A little programming / coding knowledge is required
Curiosity to learn AI field

Last Updated 7/2023

Files:

LangChain MasterClass-Develop 7 OpenAI LLM Apps using Python [TutsNode.net] - LangChain MasterClass-Develop 7 OpenAI LLM Apps using Python 10. Memory Module Concept
  • 2. Different Types of Memory.mp4 (183.1 MB)
  • 1.1 Memory Module.ipynb (369.2 KB)
  • 1. Importance of Memory in LLM powered Apps.srt (20.3 KB)
  • 2. Different Types of Memory.srt (18.7 KB)
  • 1. Importance of Memory in LLM powered Apps.mp4 (144.1 MB)
  • 2.1 Memory Module.ipynb (369.2 KB)
8. Prompt Module Concept & Implementation Using Python
  • 3.1 Example Selectors Implementation Using Python.ipynb (28.6 KB)
  • 2. Prompt Template Walkthrough.srt (19.8 KB)
  • 5. Output Parsers Walkthrough.srt (16.1 KB)
  • 3. Example Selectors Walkthrough.srt (16.1 KB)
  • 2.1 Prompt Template Implementation Using Python.ipynb (15.4 KB)
  • 4. Adding More Examples To Input Prompt.srt (9.6 KB)
  • 5.1 Output Parsers Implementation Using Python.ipynb (9.0 KB)
  • 1. Prompts Module Introduction.srt (4.3 KB)
  • 3. Example Selectors Walkthrough.mp4 (132.7 MB)
  • 2. Prompt Template Walkthrough.mp4 (127.2 MB)
  • 4. Adding More Examples To Input Prompt.mp4 (91.5 MB)
  • 5. Output Parsers Walkthrough.mp4 (90.5 MB)
  • 1. Prompts Module Introduction.mp4 (18.8 MB)
7. Project #3 - Find Similar Things App For Kids
  • 4. Let's build Similar Words Finder Application.srt (26.6 KB)
  • 4. Let's build Similar Words Finder Application.mp4 (170.4 MB)
  • 3.1 Embeddings Example using Python.zip (18.4 KB)
  • 2.1 Embeddings Practical Implementation using Python.zip (16.7 KB)
  • 3. Embeddings Example using Python.srt (16.5 KB)
  • 2. Text Embeddings Practical Implementation using Python.srt (5.3 KB)
  • 3. Embeddings Example using Python.mp4 (147.7 MB)
  • 1. Text Embedding Walkthrough.srt (8.1 KB)
  • 4.1 Let's build Similar Words Finder Application.zip (2.4 KB)
  • 2. Text Embeddings Practical Implementation using Python.mp4 (43.9 MB)
  • 1. Text Embedding Walkthrough.mp4 (34.1 MB)
3. Demo & Environment Setup
  • 1. A LangChain Example - Implementation Demo.srt (9.9 KB)
  • 2. Anaconda Installation.srt (6.4 KB)
  • 1. A LangChain Example - Implementation Demo.mp4 (53.0 MB)
  • 2. Anaconda Installation.mp4 (33.2 MB)
9. Project #4 - Marketing Campaign App
  • 6. Project Source Code.html (0.1 KB)
  • 3. Integration of Frontend & Backend.srt (12.5 KB)
  • 1. Convert Jupyter Notebook to Python Script.srt (12.1 KB)
  • 4. Modularization of Code.srt (9.4 KB)
  • 5.1 app.py (8.9 KB)
  • 2. Building the App's frontend.srt (6.5 KB)
  • 5. Adding Examples - Kids, Adult & Senior Citizen.srt (4.5 KB)
  • 6.1 Project 4 - Final Code.zip (4.4 KB)
  • 4.1 app - version 4.py (4.4 KB)
  • 3.1 app - version 3.py (4.1 KB)
  • 2.1 app - version 2.py (3.9 KB)
  • 1.1 app - version 1.py (3.3 KB)
  • 1. Convert Jupyter Notebook to Python Script.mp4 (100.8 MB)
  • 3. Integration of Frontend & Backend.mp4 (100.7 MB)
  • 4. Modularization of Code.mp4 (79.5 MB)
  • 2. Building the App's frontend.mp4 (47.7 MB)
  • 5. Adding Examples - Kids, Adult & Senior Citizen.mp4 (40.3 MB)
11. Project #5 - ChatGPT Clone with Summarization Option
  • 8. Source Code.html (0.0 KB)
  • 3. Implementing the Frontend.srt (9.6 KB)
  • 6. Implementing Chatbot Conversational View.srt (8.5 KB)
  • 5. Passing Dynamic Data.srt (6.7 KB)
  • 7. Conversation Summarization & API key feature.srt (5.2 KB)
  • 4. Modularizing the Code.srt (4.5 KB)
  • 2. Setting up the Project.srt (4.2 KB)
  • 1. ChatGPT Clone Demo.srt (2.2 KB)
  • 8.1 ChatGPT Clone - Source Code.zip (1.4 KB)
  • 3. Implementing the Frontend.mp4 (71.9 MB)
  • 6. Implementing Chatbot Conversational View.mp4 (53.7 MB)
  • 2. Setting up the Project.mp4 (43.1 MB)
  • 7. Conversation Summarization & API key feature.mp4 (37.8 MB)
  • 5. Passing Dynamic Data.mp4 (37.2 MB)
  • 4. Modularizing the Code.mp4 (34.3 MB)
  • 1. ChatGPT Clone Demo.mp4 (8.2 MB)
6. Project #2 - Simple Conversational App
  • 3. Let's Build Simple Conversational Application.srt (19.9 KB)
  • 1. Chat Model Walkthrough.srt (2.2 KB)
  • 2. Chat Model Practical Implementation using Python.srt (14.0 KB)
  • 3.1 Let's Build Simple Conversational Application.zip (1.9 KB)
  • 2.1 Chat Model Practical Implementation using Python.zip (3.4 KB)
  • 3. Let's Build Simple Conversational Application.mp4 (116.1 MB)
  • 2. Chat Model Practical Implementation using Python.mp4 (77.6 MB)
  • 1. Chat Model Walkthrough.mp4 (9.2 MB)
4. Models Module Concept
  • 1. LangChain's Modules Overview.srt (1.1 KB)
  • 1. LangChain's Modules Overview.mp4 (6.2 MB)
5. Project #1 - Simple Question & Answer App
  • 4.1 Lets' Build Simple Question Answering Application.zip (2.0 KB)
  • 4. Lets' Build Simple Question Answering Application.srt (15.3 KB)
  • 2. LLM Practical Implementation using Python.srt (13.6 KB)
  • 3. Project Environment Setup.srt (9.0 KB)
  • 1. LLMs Walkthrough.srt (5.3 KB)
  • 2.1 LLM Practical Implementation using Python.zip (3.1 KB)
  • 2. LLM Practical Implementation using Python.mp4 (91.9 MB)
  • 4. Lets' Build Simple Question Answering Application.mp4 (81.2 MB)
  • 3. Project Environment Setup.mp4 (61.1 MB)
  • 1. LLMs Walkthrough.mp4 (27.2 MB)
2. OpenAI Introduction
  • 1. What is OpenAI.srt (7.9 KB)
  • 2. OpenAI API Key Generation.srt (5.6 KB)
  • 1. What is OpenAI.mp4 (54.0 MB)
  • 2. OpenAI API Key Generation.mp4 (36.6 MB)
1. LangChain Introduction
  • 1. What is LangChain.srt (6.5 KB)
  • 2. Let's understand the LangChain benefits.srt (6.0 KB)
  • 1. What is LangChain.mp4 (45.7 MB)
  • 2. Let's understand the LangChain benefits.mp4 (37.6 MB)

Code:

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