IA - Busca Semântica de Textos com S-BERT, TF-IDF e LSA/LSI

Explore the power of Artificial Intelligence with this comprehensive AI Bootcamp! Dive deep into Natural Language Processing (NLP) using Python and master techniques like S-BERT, TF-IDF, and LSA/LSI. You'll build a practical semantic search engine for text, tackling a real-world challenge in contract analysis.

Here's what you'll learn:

• Data Science Fundamentals: Build a strong foundation in core Data Science concepts.
• Machine Learning Basics: Understand the principles of Machine Learning and its applications.
• Natural Language Processing (NLP) Essentials: Gain expertise in NLP techniques for text analysis.
• Word Embeddings & Text Preprocessing: Learn about Word Embeddings, Stopwords, Lemmatization, Stemming, and data Anonymization.
• Keyword Search vs. Semantic Search: Distinguish between traditional keyword-based search and advanced semantic text search.
• Data Science Practice: Apply Data Science methodologies to understand problems, prepare data, perform statistical analysis, and explore data insights.
• CRISP-DM Project Methodology: Follow the CRISP-DM framework for structured project development.

Project-Based Learning:

• Phase 1: Business Understanding: Define the problem, create an elevator pitch, understand the application context, identify user pain points, and define value delivery.
• Phase 2: Data Acquisition: Source data from public datasets for data science and the Brazilian Open Data Portal, understanding Open Knowledge principles.
• Phase 3: Data Preprocessing: Clean and transform data using Pandas and Numpy, including data anonymization.
• Phase 4: Exploratory Data Analysis (EDA): Visualize data insights with compelling graphs using Plotly.
• Phase 5: Semantic Search Implementation: Implement semantic search engines using S-BERT, TF-IDF, and LSA/LSI in Python.
• Phase 6: Results Evaluation: Assess the performance of your search engine based on accuracy, performance, and user satisfaction.

Practical Project: Develop text search mechanisms using Machine Learning within Google Colab, applying various techniques. This hands-on experience will equip you with the skills to build intelligent text-based applications.