This course will help us to evaluate and compare the models we have developed in previous courses. So far we have developed techniques for regression and classification, but how low should the error of a classifier be (for example) before we decide that the classifier is "good enough"? Or how do we decide which of two regression algorithms is better?
Este curso forma parte de Programa especializado: Python Data Products for Predictive Analytics
5531 ya inscrito
ofrecido por
Programa especializado: Python Data Products for Predictive AnalyticsUniversidad de California en San DiegoAcerca de este Curso
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Aprox. 9 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
Qué aprenderás
Understand the definitions of simple error measures (e.g. MSE, accuracy, precision/recall).
Evaluate the performance of regressors / classifiers using the above measures.
Understand the difference between training/testing performance, and generalizability.
Understand techniques to avoid overfitting and achieve good generalization performance.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Aprox. 9 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad de California en San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Programa - Qué aprenderás en este curso
3 horas para completar
Week 1: Diagnostics for Data
For this first week, we will go over the syllabus, download all course materials, and get your system up and running for the course. We will also introduce the basics of diagnostics for the results of supervised learning.
3 horas para completar
6 videos (Total 49 minutos), 4 lecturas, 3 cuestionarios
2 horas para completar
Week 2: Codebases, Regularization, and Evaluating a Model
This week, we will learn how to create a simple bag of words for analysis. We will also cover regularization and why it matters when building a model. Lastly, we will evaluate a model with regularization, focusing on classifiers.
2 horas para completar
4 videos (Total 35 minutos)
2 horas para completar
Week 3: Validation and Pipelines
This week, we will learn about validation and how to implement it in tandem with training and testing. We will also cover how to implement a regularization pipeline in Python and introduce a few guidelines for best practices.
2 horas para completar
4 videos (Total 24 minutos)
2 horas para completar
Final Project
In the final week of this course, you will continue building on the project from the first and second courses of Python Data Products for Predictive Analytics with simple predictive machine learning algorithms. Find a dataset, clean it, and perform basic analyses on the data. Evaluate your model, validate your analyses, and make sure you aren't overfitting the data.
2 horas para completar
2 lecturas
Reseñas
- 5 stars58,69 %
- 4 stars23,91 %
- 3 stars13,04 %
- 2 stars4,34 %
Principales reseñas sobre MEANINGFUL PREDICTIVE MODELING
por IS16 de nov. de 2019
Excellent content, but presentation is a bit challenging at times.
por PT31 de mar. de 2021
The course provided a lot of insights into predictive modeling.
Acerca de Programa especializado: Python Data Products for Predictive Analytics
Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego.
Preguntas Frecuentes
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¿Hay ayuda económica disponible?
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