Semantic Search API with S-BERT and Search API with RAG/LLM

About this course

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.</

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