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?
Ce cours fait partie de la Spécialisation Python Data Products for Predictive Analytics
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Spécialisation Python Data Products for Predictive AnalyticsUniversité de Californie à San DiegoÀ propos de ce cours
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Cours 3 sur 4 dans le
Niveau intermédiaire
Approx. 9 heures pour terminer
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Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Ce que vous allez apprendre
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.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 4 dans le
Niveau intermédiaire
Approx. 9 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Offert par
Université de Californie à 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.
Programme de cours : ce que vous apprendrez dans ce cours
3 heures pour terminer
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 heures pour terminer
6 vidéos (Total 49 min), 4 lectures, 3 quiz
2 heures pour terminer
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 heures pour terminer
4 vidéos (Total 35 min)
2 heures pour terminer
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 heures pour terminer
4 vidéos (Total 24 min)
2 heures pour terminer
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 heures pour terminer
2 lectures
Avis
- 5 stars58,69 %
- 4 stars23,91 %
- 3 stars13,04 %
- 2 stars4,34 %
Meilleurs avis pour MEANINGFUL PREDICTIVE MODELING
par IS16 nov. 2019
Excellent content, but presentation is a bit challenging at times.
par PT31 mars 2021
The course provided a lot of insights into predictive modeling.
À propos du Spécialisation 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.
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