This course 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 course will introduce you to problem definition and data preparation in a machine learning project.
Este curso forma parte de Programa Especializado - Machine Learning: Algorithms in the Real World
ofrecido por
Programa Especializado - Machine Learning: Algorithms in the Real WorldAlberta Machine Intelligence InstituteAcerca de este Curso
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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 7 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (de Brasil), Ruso (Russian), Inglés (English), Español (Spanish)
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 7 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (de Brasil), 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
3 horas para completar
Introduction to Machine Learning Applications
This week, you will learn about what machine learning (ML) actually is, contrast different problem scenarios, and explore some common misconceptions about ML. You will apply this knowledge by identifying different components essential to a machine learning business solution.
3 horas para completar
12 videos (Total 44 minutos), 6 lecturas, 2 cuestionarios
12 videos
Instructor Introduction1m
Introduction to Course 12m
What is Artificial Intelligence and Machine Learning?5m
What about Data Science?3m
The Machine Learning Process4m
The Three Kinds of Machine Learning3m
Classification: What is it and how does it work?3m
Regression: Fitting lines and predicting numbers3m
Unsupervised Learning4m
Reinforcement Learning6m
Weekly Summary1m
6 lecturas
What about Deep Learning? (supplemental)10m
Fooling Neural Networks (supplemental)10m
How to Curate A Ground Truth For Your Business Dataset (Required)10m
Learning From Multiple Annotators: A Survey (supplemental)10m
Inferring the Ground Truth Through Crowdsourcing (supplemental)10m
Semi Supervised Learning (required)10m
2 ejercicios de práctica
Concepts and Definitions20m
Identifying Machine Learning Techniques10m
2 horas para completar
Machine Learning in the Real World
This week, you will learn how to translate a business need into a machine learning problem. We'll walk through some applied examples so you can get a feel for what makes a well-defined question for your QuAM. Narrowing down your question and making sure you have the data necessary to learn is critical to ML success!
2 horas para completar
8 videos (Total 34 minutos), 4 lecturas, 1 cuestionario
8 videos
Features and transformations of raw data6m
Farmer Betty and Her Precision Agriculture Plans3m
What to consider when using your QuAM2m
Broad Examples Narrowed Down4m
Identify Business Evaluation4m
Everything is a Proxy4m
Weekly Summary2m
4 lecturas
A Brief Introduction into Precision Agriculture10m
Farmer Betty Tried Unsupervised Learning (required)10m
Data is Central to Your ML Problem (required)10m
Martin Zinkevich's Rules for ML (supplemental)10m
1 ejercicio de práctica
Machine Learning in the Real World Review
1 hora para completar
Learning Data
This week is all about data. You will learn about data acquisition and understand the various sources of training data. We'll talk about how much data you need and what pitfalls might arise, including ethical issues.
1 hora para completar
9 videos (Total 34 minutos), 2 lecturas, 1 cuestionario
9 videos
How Much Data Do I Need?4m
Ethical Issues4m
Bias in Data Sources3m
Noise and Sources of Randomness5m
Image Classification Example3m
Data Cleaning: Everybody's favourite task4m
Why you need to set up a Data Pipeline4m
Weekly Summary1m
2 lecturas
Data Protection Laws (required)10m
Government readings on data privacy (supplemental)10m
1 ejercicio de práctica
Understanding Data for ML
1 hora para completar
Machine Learning Projects
This week you will learn about the Machine Learning Process Lifecycle (MLPL). After understanding the definitions and components of the MLPL you will analyze the application of the MLPL on a case study.
1 hora para completar
7 videos (Total 35 minutos), 2 lecturas, 1 cuestionario
7 videos
MLPL as experienced by Farmer Betty3m
Exploring the process of problem definition7m
Assessing your QuAM for use in your Business6m
Technically Assessing the Strength of your QuAM6m
Different Kinds of Wrong4m
Weekly Summary2m
2 lecturas
Machine Learning Process Lifecycle Explained10m
Deep Learning for Identifying Metastatic Breast Cancer (advanced supplemental)10m
1 ejercicio de práctica
Understanding Machine Learning Projects
Reseñas
Principales reseñas sobre INTRODUCTION TO APPLIED MACHINE LEARNING
por SR8 de oct. de 2020
I have been teaching Machine Learning for some time now. This course is really good and comprehensively presents the working of machine learning process in a nutshell. Very good introductory course.
por MM28 de oct. de 2019
I have really got benefit from this course as a beginner to ML, it gives me the best understanding of ML. I m looking forward to getting into it more efficiently with more practices.
por BW12 de nov. de 2020
An excellent introduction to the mechanics of ML. Not so deep that coding is required, but simultaneously not so high-level as to be abstract. A very nice intro - thanks for this!
por HL21 de jun. de 2020
An excellent introduction to the fascinating world of machine learning and its endless applications. Loved the emphasis on the evaluation of the business prospect of ML as well.
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.
Preguntas Frecuentes
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