Welcome to the AI Labs! This repository contains the lab work for the course, covering fundamental Python, essential libraries like Pandas and NumPy, working with Kaggle datasets, and advanced AI tasks using Hugging Face.
- Introduction to Python syntax
- Variables, data types, and operators
- Control structures: if-else, loops
- Functions and modules
- File handling in Python
- Introduction to Pandas and NumPy
- Data manipulation using Pandas DataFrame
- Basic operations with NumPy arrays
- Data cleaning and analysis
- Performing mathematical operations with NumPy
- Introduction to Kaggle datasets
- Downloading datasets from Kaggle
- Exploring and visualizing data
- Basic data preprocessing
- Applying machine learning models on Kaggle datasets
- Introduction to Hugging Face
- Using pre-trained models for text summarization
- Implementing text summarization using Hugging Face transformers
- Fine-tuning models for better performance
- Evaluating summarization results
- Clone this repository to your local machine:
git clone https://github.com/Jamil226/FA24-AI.git
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
FOSS - Free and Open Source Licenses
MIT - Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so.