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
Introduction to Applied Machine Learning
ofrecido por
Programa Especializado - Machine Learning: Algorithms in the Real WorldAlberta Machine Intelligence Institute
Acerca de este Curso
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Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 9 horas para completar
Sugerido: 13 hours/week
Inglés (English)
Subtítulos: Inglés (English)
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
1 hora 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!
1 hora 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
Revisiones
Principales revisiones sobre INTRODUCTION TO APPLIED MACHINE LEARNING
por MMOct 28, 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 AASep 11, 2019
very comprehensive course on applied machine learning. the most interesting information in this course is business needs for ML and what it's requirement to have a good QuAM.
por KSOct 13, 2019
This course will give the actual understanding especially focusing on different types of Machine learning with real examples. I'm so excited to learn more about it.
por VESep 21, 2019
I have taken a great deal of knowledge in this course and have applied it to what I have seen in the ML and AI world. This was a great introduction!
por PRSep 27, 2019
I enjoyed this course. It was a good refresher but I believe that it is also good for people that want to understand this Machine Learning hype...
por OHOct 24, 2019
This course was very helpful and fruitful. It is a good entry for machine learning and I really recommend it. Thanks, Anna, Thanks, amii
por BTJan 5, 2020
Course gives a broader understanding of any Machine Learning project, how to approach and what are the important things to keep in mind.
por FMNov 11, 2019
Great Introductory course, it was delivered very good. I picked up a lot of different definitions which were simplified. Very Good!
por UJan 24, 2020
The course was a really good one introducing you to the machine learning and how you should think and approach an ML problem.
por MTAug 30, 2019
Anna Koop has a very engaging onscreen personality that makes it easy to follow her explanations of machine learning.
por AHMar 29, 2020
It is a good start. For sure, this course is recommended for everyone who is not in the computer science world.
por ECSep 21, 2019
Very informative, highly recommended to anyone with an interest in starting any ML project in the future.
Acerca de 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
research institute that pushes the bounds of academic knowledge and guides business understanding of artificial intelligence and machine learning.
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.
After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results, and deploy it in the real world. You will also be able to anticipate and mitigate common pitfalls in applied machine learning.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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¿Hay ayuda económica disponible?
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