GENAI Workshop - Conducted by INVENTIA (GDG) on Campus KARE

This repository contains materials and resources from the GENAI Workshop conducted by INVENTIA, in collaboration with Google Developer Group (GDG) at the Kalasalingam Academy of Research and Education (KARE). The workshop focused on applying NLP techniques and using generative AI models from Hugging Face and Google AI Studio.

Workshop Overview

Day 1

1. Data Preprocessing using NLP

Participants were introduced to data preprocessing techniques for Natural Language Processing (NLP). This session covered:

• Tokenization
• Stop word removal
• Stemming and lemmatization
• Text cleaning

2. SMS Spam Prediction using NLP and Naive Bayes

The second session focused on building a spam prediction model using:

• Preprocessing techniques discussed earlier
• Training a Naive Bayes classifier for SMS spam detection
• Evaluating model performance with accuracy metrics

Day 2

1. Using Different Models with Hugging Face API Keys

Participants explored various NLP models using Hugging Face. This session covered:

• Setting up Hugging Face API keys
• Selecting pre-trained models for specific NLP tasks
• Running inference on text inputs using different models

2. Generative Model for Text and Image Generation using Google AI Studio API

The final session involved working with Google AI Studio API to:

• Create a generative model for text and image generation
• Integrate the model with external applications
• Experiment with custom fine-tuning for generative tasks

Technologies Used

• Python
• Hugging Face Transformers
• Google AI Studio
• Natural Language Processing (NLP)
• Naive Bayes Classifier
• Generative AI

How to Use This Repository

1. Clone this repository to your local machine:

   git clone https://github.com/yourusername/genai-workshop.git
   cd genai-workshop

2. You can use Google Colab to execute the above notebooks

3. Explore the notebooks directory for Jupyter notebooks with code examples from the workshop.

4. Refer to the data directory for sample datasets used in the sessions.

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests if you'd like to improve the materials or add new examples.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any inquiries, reach out to the event organizers at:

• Email: 99220040901@klu.ac.in
• GDG Community Page: GDG INVENTIA
• GDG Community Chennai Lead: N Hema Priya
• Linkedin : N Hemapriya