No-code AI applications with ChatGPT, OpenAI, Flowise & LLMs

سرفصل های دوره

Develop ChatGPT and LLM applications without programming skills using ChatGPT, Flowise, LangChain, Llama, Pinecone...

1. Introduction to Language Models

1. Introduction to Language Models

2. What are Language Models

3. Types of Language Models

2. Introduction to ChatGPT

1. OpenAI, the company behind the ChatGPT algorithm

2. Introduction to ChatGPT

3. Advantages of ChatGPT and difference with conventional ChatBots

4. Limitations of ChatGPT

3. Tools for LLM and NLP

1. Tools for working with LLMs and NLPs

2. Open AI API

3. Hands-on Lab OpenAI API

4. Hugging Face Fundamentals

5. LangChain Fundamentals

6. Open-source LLM models

4. AI Application Development with ChatGPT with LangChain

1. Introduction to LangChain

2. Different LangChain model types and requirements

3. LLM input management with LangChains Prompts Module

4. Combination of LLM with other components through chains

5. Providing access to external data through LangChain Indexes

6. Giving ChatGPT the ability to memorize through the LangChain Memory

7. Providing access to tools through LangChains Agents module

5. Application Development with ChatGPT without code with Flowise

1. Developing state-of-the-art LLMs

2. Flowise Features

3. Installation of Flowise

4. Getting started with Flowise

6. Flowise components

1. Flowise components

2. Flowise Modeling Component

3. Flowise Prompts Component

4. Vector Stores, Indices, Embeddings and Document Loaders of Flowise

5. Flowise Memory Component

6. Flowise Chain Component

7. Flowise Agents and Tools

7. Flowise Practical Project (Part I)

1. Practical Exercise Designing the customized wizard

2. Solution Customized wizard design

3. Practical Exercise Basic ChatFlow Development

4. Solution Basic ChatFlow Development

5. Practical Exercise Development of an Assistant

6. Solution Development of an Assistant

8. LLM Model Training

1. Different variants of LLMs and how to select them

2. Data privacy in ChatGPT training

9. LLM training with your own documents

1. Fundamentals of LLM training with documents

2. Lab Adding the QA Chain, Vector Store and PDF Loader

3. Lab Adding Text Splitter and OpenAI Embeddings

10. Vector Databases

1. Introduction to vector databases and importance for LLMs

2. Characteristics of vector databases

3. Different Vector Databases

4. Pinecone Fundamentals

5. Adding Pinecone Vector Estore

6. Loading Embeddings and Indexes from Pinecone

11. Flowise Practical Project (Part II)

1. Practical Exercise Developing Indexes and Embeddings for Pinecone

2. Solution Creating Vectors and Indexes in Pinecone

3. Practical Exercise Development of a Customized LLM

4. Solution Development of a customized LLM

5. Practical Exercise Putting into Production

6. Solution Production deployment of the Custom LLM

12. Multi-stage reasoning

1. Multi-step reasoning

2. Linking two large language models (LLM)

3. Chaining a third language model

13. Hugging Face and the integration of Hugging Face in Flowise

1. Introduction to Hugging Face and its components

2. Hugging Face interface and model and dataset selection

3. Tokenizer and Hugging Face Models

4. Hugging Face Datasets

5. Practical Lab Use of models from Hugging Face

6. Practical Lab Consuming the Hugging Face model from Python

7. Practical Laboratory Using Hugging Face models from Flowise

14. Open-source Large Language Models (LLMs)

1. Benefits of open-source LLM models

2. Different open-source LLM models and comparative analysis

3. Fundamentals of the Llama model

4. Alpaca model fundamentals

5. Fundamentals of the Vicuna model

6. Downloading and initialization of the model with Docker, LocalAI and GPT4All

7. Using the LLM Open Source model from Flowise

8. Advanced Project with Local AI LLama2, Faiss and Local AI Embeddings

15. Falcon the most powerful Open-Source model to date

1. Fundamentals of the Falcon model

2. Practical Lab Using the Falcon 7b model from Flowise

3. Practical Lab Using the Falcon 40b model from Flowise

16. Open-Source Cloud Models with Replicate

1. Replicate Basics

2. Using LLM Open-source Llama, Vicuna and Falcon through Replicate

3. Use of Replicates Llama2 model through Flowise

17. Flowise Credentials

1. Credential management in Flowise

18. Auto-GPT the AI that outperformed ChatGPT

1. Introduction to Auto-GPT

2. Auto-GPT, BabyAGI and Jarvis models

3. Practical Lab Using Auto-GPT

4. Hands-on Lab Auto-GPT Basics in Flowise

5. Hands-on Lab Using Auto-GPT from Flowise

6. Baby AGI the evolution of the AutoGPT model

19. Putting Flowise models into production

1. Production Deployment of LLMs

2. Putting into Production through APIs

3. Adding credentials to APIs

4. Querying PDF files using Flowise APIs

20. Project from start to finish

1. Web Scrapper, Pinecone and Conversational Retrieval QA Chain

2. Improving the Web Scrapper and avoiding model hallucinations

3. Alternative project configuration

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تولید کننده: Udemy