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.
Ce cours fait partie de la Spécialisation TensorFlow: Data and Deployment
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Spécialisation TensorFlow: Data and Deploymentdeeplearning.aiÀ propos de ce cours
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Cours 1 sur 4 dans le
Niveau intermédiaire
Basic understanding of JavaScript
Approx. 22 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Ce que vous allez apprendre
Train and run inference in a browser
Handle data in a browser
Build an object classification and recognition model using a webcam
Compétences que vous acquerrez
- Convolutional Neural Network
- Machine Learning
- Tensorflow
- Object Detection
- TensorFlow.js
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 1 sur 4 dans le
Niveau intermédiaire
Basic understanding of JavaScript
Approx. 22 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Offert par
deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Programme de cours : ce que vous apprendrez dans ce cours
7 heures pour terminer
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 heures pour terminer
11 vidéos (Total 30 min), 7 lectures, 5 quiz
5 heures pour terminer
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 heures pour terminer
8 vidéos (Total 27 min), 5 lectures, 3 quiz
5 heures pour terminer
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 heures pour terminer
12 vidéos (Total 28 min), 6 lectures, 3 quiz
5 heures pour terminer
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 heures pour terminer
11 vidéos (Total 26 min), 3 lectures, 3 quiz
Avis
Meilleurs avis pour BROWSER-BASED MODELS WITH TENSORFLOW.JS
par JG19 déc. 2020
Excellent course!!! It is actually a milestone for people like me who have trained models in Jupyter notebooks, but Tensorflow JS is actually a great way for the models to become 'alive'! Thanks!
par EJ17 mars 2021
This course is very practical and interesting. I enjoyed the excitement I got along the way.\n\nIt was modeled to make you pass as long as you want to pass.\n\nThank you Laurence and Andrew.
par AZ28 mars 2020
No doubt, the team of Deeplearning.AI is building best learning resources. We would love to get more and more resources for easy way learning from DeepLearning.AI Team. Thanks to all.
par SA7 juil. 2020
course contents are good and explained very well with one problem of audio, audio is not clear and pitch is low but I like this course. as a beginner, this course is best.
À propos du Spécialisation 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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