Malaria parasite detection using ensemble learning in Keras
Offered By: Coursera Project Network via Coursera
Course Description
Overview
In this 1-hour long project-based course, you will learn what ensemble learning is and how to implement is using python. You will create deep convolutional neural networks using the Keras library to predict the malaria parasite. You will learn various ways of assessing classification models. You will create an ensemble of deep convolutional neural networks and apply voting in order to combine the best predictions of your models.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Syllabus
- Project Overview
- Ensemble learning lets you achieve higher predictive performance by combining a group of machine learning models and picking the best predictions of the group, or the "ensemble". In this project you will learn what ensemble learning is and how to implement is using python. You will create deep convolutional neural networks using the Keras library to predict the malaria parasite. You will learn various ways of assessing classification models. You will create an ensemble of deep convolutional neural networks and apply voting in order to combine the best predictions of your models.
Taught by
Sherif A. Tawfik Abbas
Related Courses
Machine Learning 1—Supervised LearningBrown University via Udacity Data Mining: Theories and Algorithms for Tackling Big Data | 数据挖掘:理论与算法
Tsinghua University via edX Big Data Applications: Machine Learning at Scale
Yandex via Coursera Data Analytics Foundations for Accountancy II
University of Illinois at Urbana-Champaign via Coursera PyCaret: Anatomy of Classification
Coursera Project Network via Coursera