Bienvenidos
IPN-Dharma IA Lab
Es una iniciativa de Laboratorio de Inteligencia Artificial del CIC del IPN con la colaboración de DHARMA para motivar a investigadores, profesores y estudiantes a aprovechar los cursos, recursos y herramientas de las principales plataformas tecnológicas de la industria en las áreas de Aprendizaje Automático, Ciencia de Datos, Computación en la Nube, Inteligencia Artificial e Internet de las Cosas con el propósito de generar una experiencia práctica a través de un modelo de aprendizaje entre pares y por objetivos.
Nivel 1: Alfabetización y Fundamentos
Predict Rocket Launch Delays with Machine Learning
This learning path introduces you to the world of machine learning. You'll take a real-life problem that NASA faces and apply machine learning to solve it. The goal is to get students excited and curious to discover how machine learning could help solve other problems in space discovery and different aspects of life.
Cursos en este programa
1) Introduction to Rocket Launches
Get an introduction to how NASA chooses a date for a rocket launch and discover machine learning fundamentals.
In this module, you'll begin to discover:
In this module, you'll begin to discover:
- The challenges weather can pose for a rocket launch.
- The data science lifecycle.
- How machine learning works.
- The role ethics play in machine learning.
Esfuerzo estimado 1 hora
Idioma inglés
2) Data Collection and Manipulation
Learn about the steps to import data into Python and clean the data for use in creating machine learning models.
In this module, you will:
In this module, you will:
- Explore weather data on days crewed and uncrewed rockets were launched.
- Explore weather data on the days surrounding launch days.
- Clean the data in preparation for training the machine learning model.
3) Build a Machine Learning Model
In this module you focus on a local analysis of your data by using scikit-learn, and use a decision tree classifier to gain knowledge from raw weather and rocket launch data.
In this module, you'll begin to discover:
In this module, you'll begin to discover:
- The importance of column choosing.
- How to split data to effectively train and test a machine learning algorithm.
- How to train, test, and score a machine learning algorithm.
- How to visualize a tree classification model.