This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally used. Learners will also gain skills to contrast the practical consequences of different data preparation steps and describe common production issues in applied ML.
Este curso forma parte de Programa especializado: Machine Learning: Algorithms in the Real World
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Programa especializado: Machine Learning: Algorithms in the Real WorldAlberta Machine Intelligence InstituteAcerca de este Curso
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Fechas límite flexibles
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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
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Aprox. 9 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
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.
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
Alberta Machine Intelligence Institute
The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based
Programa - Qué aprenderás en este curso
4 horas para completar
Classification using Decision Trees and k-NN
Welcome to Supervised Learning, Tip to Tail! This week we'll go over the basics of supervised learning, particularly classification, as well as teach you about two classification algorithms: decision trees and k-NN. You'll get started programming on the platform through Jupyter notebooks and start to familiarize yourself with all the issues that arise when using machine learning for classification.
4 horas para completar
8 videos (Total 46 minutos), 4 lecturas, 2 cuestionarios
2 horas para completar
Functions for Fun and Profit
Welcome to the second week of the course! In this week you'll learn all about regression algorithms, the other side of supervised learning. We'll introduce you to the idea of finding lines, optimization criteria, and all the associated issues. Through regression we'll see the interactions between model complexity and accuracy, and you'll get a first taste of how regression and classification might relate.
2 horas para completar
9 videos (Total 62 minutos), 1 lectura, 4 cuestionarios
3 horas para completar
Regression for Classification: Support Vector Machines
This week we'll be diving straight in to using regression for classification. We'll describe all the fundamental pieces that make up the support vector machine algorithms, so that you can understand how many seemingly unrelated machine learning algorithms tie together. We'll introduce you to logistic regression, neural networks, and support vector machines, and show you how to implement two of those.
3 horas para completar
6 videos (Total 34 minutos), 1 lectura, 2 cuestionarios
1 hora para completar
Contrasting Models
Now at the tail end of the course, we're going to go over how to know how well your model is actually performing and what you can do to get even better performance from it. We'll review assessment questions particular to regression and classification, and introduce some other tools that really help you analyze your model performance. The topics covered this week aim to give you confidence in your models, so you're ready to unlock the power of machine learning for your business goals.
1 hora para completar
8 videos (Total 46 minutos), 1 lectura, 1 cuestionario
Reseñas
- 5 stars76,05 %
- 4 stars18,45 %
- 3 stars3,24 %
- 2 stars0,99 %
- 1 star1,24 %
Principales reseñas sobre MACHINE LEARNING ALGORITHMS: SUPERVISED LEARNING TIP TO TAIL
por DS6 de may. de 2020
Excellent course for an overview of different ML algorithms. The course is made from a perspective of giving insights in process and not too many mathematical details.
por BS4 de oct. de 2020
Excellent instruction. One of the best in ML. Could use a bit more python though.
por TH14 de may. de 2022
This is an excellent course which goes into some depth on the different ML models and underlying complexity but it avoids getting bogged down into the details too much.
por CW29 de sep. de 2020
Great course, easy to grasp the main idea of how to assess and tune the performance of question-answering machines learned by machine learning algorithms through data
Acerca de Programa especializado: Machine Learning: Algorithms in the Real World
This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application.
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