In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it. Learners will then present a project report to demonstrate the validity of their model and their proficiency in the field of Deep Learning.
Dieser Kurs ist Teil der Spezialisierung IBM AI Engineering Zertifikat über berufliche Qualifikation
von
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57,985 kürzliche Aufrufe
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 6 von 6 in
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Fortgeschritten“
Ca. 16 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 6 von 6 in
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Fortgeschritten“
Ca. 16 Stunden zum Abschließen
Englisch
Untertitel: Englisch
von
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Lehrplan - Was Sie in diesem Kurs lernen werden
3 Stunden zum Abschließen
Module 1 - Loading Data
In this module, you will get introduced to the problem that we will try to solve throughout the course. You will also learn how to load the image dataset, manipulate images, and visualize them.
3 Stunden zum Abschließen
4 Videos (Gesamt 8 min)
3 praktische Übungen
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Download Data10m
Loading Data with Keras30m
3 Stunden zum Abschließen
Module 2
In this Module, you will mainly learn how to process image data and prepare it to build a classifier using pre-trained models.
3 Stunden zum Abschließen
1 Video (Gesamt 2 min)
1 Video
2 praktische Übungen
Data loader PyTorch15m
Data Preparation with Keras30m
3 Stunden zum Abschließen
Module 3
In this Module, in the PyTorch part, you will learn how to build a linear classifier. In the Keras part, you will learn how to build an image classifier using the ResNet50 pre-trained model.
3 Stunden zum Abschließen
1 Video (Gesamt 2 min)
1 Video
2 praktische Übungen
Linear Classifier PyTorch10m
Building a Classifier with Pre-Trained Models30m
7 Stunden zum Abschließen
Module 4
In this Module, in the PyTorch part, you will complete a peer review assessment where you will be asked to build an image classifier using the ResNet18 pre-trained model. In the Keras part, for the peer review assessment, you will be asked to build an image classifier using the VGG16 pre-trained model and compare its performance with the model that we built in the previous Module using the ResNet50 pre-trained model.
7 Stunden zum Abschließen
1 Video (Gesamt 3 min), 1 Lektüre, 2 Quiz
1 Lektüre
Peer Review Instruction10m
Bewertungen
Top-Bewertungen von AI CAPSTONE PROJECT WITH DEEP LEARNING
von DO26. Mai 2020
I like the flexibility to pick our framework for the project i wish the kers one were a little bit more challenging
von RB22. Mai 2020
A very nice project based course to get hands on experience with deep learning and transfer learning.
von SK6. Mai 2020
The Course is good, The labs were crashing which were causing lot of issues in completing the course
von RB3. Juni 2020
Putting in practice what I learned and experienced positive results was very satisfactory.
Über den IBM AI Engineering Zertifikat über berufliche Qualifikation
The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence. After competing this comprehensive 6 course Professional Certificate, you will get a practical understanding of Machine Learning and Deep Learning.
You will master fundamental concepts of Machine Learning and Deep Learning, including supervised and unsupervised learning. You will utilize popular Machine Learning and Deep Learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow applied to industry problems involving object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers.
You will be able to scale Machine Learning on Big Data using Apache Spark. You will build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders.
By the end of this Professional Certificate, you will have completed several projects showcasing your proficiency in Machine Learning and Deep Learning, and become armed with skills for a career as an AI Engineer.
Häufig gestellte Fragen
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What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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