Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung TensorFlow: Data and Deployment
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Spezialisierung TensorFlow: Data and Deploymentdeeplearning.aiÜber diesen Kurs
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Kurs 1 von 4 in
Stufe „Mittel“
Basic understanding of JavaScript
Ca. 22 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Italienisch, Vietnamesisch, Deutsch, Russisch, Englisch, Spanisch
Was Sie lernen werden
Train and run inference in a browser
Handle data in a browser
Build an object classification and recognition model using a webcam
Kompetenzen, die Sie erwerben
- Convolutional Neural Network
- Machine Learning
- Tensorflow
- Object Detection
- TensorFlow.js
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 1 von 4 in
Stufe „Mittel“
Basic understanding of JavaScript
Ca. 22 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Italienisch, Vietnamesisch, Deutsch, Russisch, Englisch, Spanisch
von
deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Lehrplan - Was Sie in diesem Kurs lernen werden
7 Stunden zum Abschließen
Introduction to TensorFlow.js
Welcome to Browser-based Models with TensorFlow.js, the first course of the TensorFlow for Data and Deployment Specialization. In this first course, we’re going to look at how to train machine learning models in the browser and how to use them to perform inference using JavaScript. This will allow you to use machine learning directly in the browser as well as on backend servers like Node.js. In the first week of the course, we are going to build some basic models using JavaScript and we'll execute them in simple web pages.
7 Stunden zum Abschließen
11 Videos (Gesamt 30 min), 7 Lektüren, 5 Quiz
5 Stunden zum Abschließen
Image Classification In the Browser
This week we'll look at Computer Vision problems, including some of the unique considerations when using JavaScript, such as handling thousands of images for training. By the end of this module you will know how to build a site that lets you draw in the browser and recognizes your handwritten digits!
5 Stunden zum Abschließen
8 Videos (Gesamt 27 min), 5 Lektüren, 3 Quiz
5 Stunden zum Abschließen
Converting Models to JSON Format
This week we'll see how to take models that have been created with TensorFlow in Python and convert them to JSON format so that they can run in the browser using Javascript. We will start by looking at two models that have already been pre-converted. One of them is going to be a toxicity classifier, which uses NLP to determine if a phrase is toxic in a number of categories; the other one is Mobilenet which can be used to detect content in images. By the end of this module, you will train a model in Python yourself and convert it to JSON format using the tensorflow.js converter.
5 Stunden zum Abschließen
12 Videos (Gesamt 28 min), 6 Lektüren, 3 Quiz
5 Stunden zum Abschließen
Transfer Learning with Pre-Trained Models
One final work type that you'll need when creating Machine Learned applications in the browser is to understand how transfer learning works. This week you'll build a complete web site that uses TensorFlow.js, capturing data from the web cam, and re-training mobilenet to recognize Rock, Paper and Scissors gestures.
5 Stunden zum Abschließen
11 Videos (Gesamt 26 min), 3 Lektüren, 3 Quiz
Bewertungen
- 5 stars81,49 %
- 4 stars14,26 %
- 3 stars2,67 %
- 2 stars0,66 %
- 1 star0,89 %
Top-Bewertungen von BROWSER-BASED MODELS WITH TENSORFLOW.JS
von RF14. Apr. 2020
Great course, the hands-on approach is great for anyone that has taken the Deeplearning Specialization from Andrew (it's mandatory, in my opinion)!
von ZZ22. Mai 2021
i like how Laurance give the explanation, but there is something that I think very bad, that is a program assisgment is complicated and takes a lot of time to complete
von DA24. Dez. 2020
I have worked with tensorflow for some time, but I didn't know it is this straight forward to deploy on browser.Very good explanation with examples of different deployment options
von TH24. März 2021
Good as a introduction for application based machine learning, however, I think the course should add more realistic example of such interesting process
Über den Spezialisierung TensorFlow: Data and Deployment
Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models.
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