Introduction to Python for IA
- General Information
- Symposia
- Atomic Layer Deposition
- Biomaterials and Polymers
- Characterization and Metrology
- Luminescence Phenomena: Materials and Applications
- Microelectronics and MEMS
- Multifunctional and Magnetic Materials
- Nanostructures
- Plasma and Vacuum
- Renewable Energy: Materials and Devices
- Semiconductors
- Tribology, Surfaces and Interfaces
- Theory and Simulation of Materials
- Thin Films
- Science Outreach
- General Program
- Plenary Lectures
- Short Courses
- Technical Talk
- Congress Registration
- Second Athletic Race Registration
- Posters
- Abstract Submission 2024
- Commitees
- Fees
- Hotel Accomodation
- Awards/Grants
- Sponsors and Exhibit
Introduction to Python for IA
Dr. Luis García, CNyN-UNAM
Known for its simplicity and versatility, Python has become the language of choice for many developers and data scientists working in the field of AI. This course explores the basic AI concepts and algorithms for creating a QSAR model using Python. After completing the course students will be able to prepare data (analyze and clean), select the best features using different strategies and build classification models. As example problem we will build a QSAR model for predict activities in small compounds.
Content:
- Environment setting
- Python scientific libraries
- Data analysis
- Feature selection algorithms
- Modeling algorithms
For taking the workshop, It is desired to have basic knowledge of Python