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In a rich Artificial Intelligence Bootcamp, learn S-BERT and RAG(LLM) through Natural Processing Language (NLP) with Python, and develop a semantic text search engine API by solving a real problem of a purchasing analysis system.
As content:
Fundamentals.
Learn the fundamentals of Data Science;
Learn the fundamentals of Machine Learning;
Learn the fundamentals of Natural Language Processing;
Learn the fundamentals of Data Cleaning, Word Embendings, Stopwords, and Lemmatization;
Learn the fundamentals of text search by keywords and semantic text search;
Practice Data Science to understand the problem, prepare the database and statistical analysis;
Practical project.
This course is divided into two modules where you will learn concepts and build a text search application in a practical way.
BERT
In this module, you will work with:
Python to develop the application;
Data cleaning techniques to prepare the database;
Using the SpaCy library for Natural Language Processing;
Generating Word Embeddings and calculating similarity for data recovery;
Transformers model for data recovery by context;
S-BERT as a semantic text search tool;
Flask and Flassger for developing APIs.
Retrieval-augmented generation (RAG)
In this module you will work with:
Python to develop the application;
Large Language Models (LLMs). Advanced AI models that understand and generate natural language;
Using the OpenAI API to build AI products
LangChain to build applications that use LLMs;
Flask and Flassger for developing APIs.
Optional module: learn how to develop API with Flask.
Welcome and have fun.
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