Machine Learning Capstone: An Intelligent Application with Deep Learning

Methode

Machine Learning Capstone: An Intelligent Application with Deep Learning

Coursera (CC)
Logo von Coursera (CC)
Bewertung: starstarstarstar_halfstar_border 7,2 Bildungsangebote von Coursera (CC) haben eine durchschnittliche Bewertung von 7,2 (aus 6 Bewertungen)

Tipp: Haben Sie Fragen? Für weitere Details einfach auf "Kostenlose Informationen" klicken.

Beschreibung

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: Have you ever wondered how a product recommender is built? How you can infer the underlying sentiment from reviews? How you can extract information from images to find visually-similar products to recommend? How you construct an application that does all of these things in real time, and provides a front-end user experience? That’s what you will build in this course! Using what you’ve learned about machine learning thus far, you will build a general product recommender system that does much more than just find similar products You will combine images of products with product descriptions and their reviews to create a truly innovative intelligent application. You’ve pr…

Gesamte Beschreibung lesen

Frequently asked questions

Es wurden noch keine Besucherfragen gestellt. Wenn Sie weitere Fragen haben oder Unterstützung benötigen, kontaktieren Sie unseren Kundenservice.

Noch nicht den perfekten Kurs gefunden? Verwandte Themen: Deep Learning, Capstone Courses, Machine Learning, Python und Data Science.

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: Have you ever wondered how a product recommender is built? How you can infer the underlying sentiment from reviews? How you can extract information from images to find visually-similar products to recommend? How you construct an application that does all of these things in real time, and provides a front-end user experience? That’s what you will build in this course! Using what you’ve learned about machine learning thus far, you will build a general product recommender system that does much more than just find similar products You will combine images of products with product descriptions and their reviews to create a truly innovative intelligent application. You’ve probably heard that Deep Learning is making news across the world as one of the most promising techniques in machine learning, especially for analyzing image data. With every industry dedicating resources to unlock the deep learning potential, to be competitive, you will want to use these models in tasks such as image tagging, object recognition, speech recognition, and text analysis. In this capstone, you will build deep learning models using neural networks, explore what they are, what they do, and how. To remove the barrier introduced by designing, training, and tuning networks, and to be able to achieve high performance with less labeled data, you will also build deep learning classifiers tailored to your specific task using pre-trained models, which we call deep features. As a core piece of this capstone project, you will implement a deep learning model for image-based product recommendation. You will then combine this visual model with text descriptions of products and information from reviews to build an exciting, end-to-end intelligent application that provides a novel product discovery experience. You will then deploy it as a service, which you can share with your friends and potential employers. Learning Outcomes: By the end of this capstone, you will be able to: -Explore a dataset of products, reviews and images. -Build a product recommender. -Describe how a neural network model is represented and how it encodes non-linear features. -Combine different types of layers and activation functions to obtain better performance. -Use pretrained models, such as deep features, for new classification tasks. -Describe how these models can be applied in computer vision, text analytics and speech recognition. -Use visual features to find the products your users want. -Incorporate review sentiment into the recommendation. -Build an end-to-end application. -Deploy it as a service. -Implement these techniques in Python.

Created by:   University of Washington
  • Taught by:    Carlos Guestrin, Amazon Professor of Machine Learning

    Computer Science and Engineering
  • Taught by:    Emily Fox, Amazon Professor of Machine Learning

    Statistics
Basic Info Course 6 of 6 in the Machine Learning Specialization. Language English How To Pass Pass all graded assignments to complete the course. Course 6 of Specialization Build Intelligent Applications. Master machine learning fundamentals in five hands-on courses. Machine Learning University of Washington Learn More Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from your peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

About University of Washington Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.

Syllabus

Werden Sie über neue Bewertungen benachrichtigt

Es wurden noch keine Bewertungen geschrieben.

Schreiben Sie eine Bewertung

Haben Sie Erfahrung mit diesem Kurs? Schreiben Sie jetzt eine Bewertung und helfen Sie Anderen dabei die richtige Weiterbildung zu wählen. Als Dankeschön spenden wir € 1,00 an Stiftung Edukans.

Es wurden noch keine Besucherfragen gestellt. Wenn Sie weitere Fragen haben oder Unterstützung benötigen, kontaktieren Sie unseren Kundenservice.

Bitte füllen Sie das Formular so vollständig wie möglich aus

Anrede
(optional)
(optional)
(optional)
(optional)
(optional)

Haben Sie noch Fragen?

(optional)
Damit Ihnen per E-Mail oder Telefon weitergeholfen werden kann, speichern wir Ihre Daten.
Mehr Informationen dazu finden Sie in unseren Datenschutzbestimmungen.