Acerca de este Curso

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100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Basic understanding of JavaScript

Aprox. 12 horas para completar

Sugerido: 4 weeks of study, 4-5 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Qué aprenderás

  • Check

    Train and run inference in a browser

  • Check

    Handle data in a browser

  • Check

    Build an object classification and recognition model using a webcam

Habilidades que obtendrás

Convolutional Neural NetworkMachine LearningTensorflowObject DetectionTensorFlow.js

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Basic understanding of JavaScript

Aprox. 12 horas para completar

Sugerido: 4 weeks of study, 4-5 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Instructor

Calificación del instructor4.75/5 (23 calificaciones)Info
Imagen del instructor, Laurence Moroney

Laurence Moroney 

AI Advocate
Google Brain
128,129 alumnos
8 cursos

ofrecido por

Logotipo de deeplearning.ai

deeplearning.ai

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

5 horas para completar

Introduction to TensorFlow.js

5 horas para completar
11 videos (Total 30 minutos), 7 lecturas, 3 cuestionarios
11 videos
Course Introduction, A Conversation with Andrew Ng1m
A Few Words From Laurence2m
Building the Model3m
Training the Model3m
First Example In Code4m
The Iris Dataset1m
Reading the Data4m
One-hot Encoding1m
Designing the NN2m
Iris Classifier In Code6m
7 lecturas
Getting Your System Ready10m
Downloading the Coding Examples and Exercises10m
Your First Model10m
Iris Dataset Documentation10m
Using the Web Server10m
Iris Classifier10m
Week 1 Wrap up10m
2 ejercicios de práctica
Quiz 1
One-Hot Encoding
Semana
2

Semana 2

4 horas para completar

Image Classification In the Browser

4 horas para completar
8 videos (Total 27 minutos), 5 lecturas, 2 cuestionarios
8 videos
Creating a Convolutional Net with JavaScript4m
Visualizing the Training Process2m
What Is a Sprite Sheet?1m
Using the Sprite Sheet2m
Using tf.tidy() to Save Memory1m
A Few Words From Laurence24s
MNIST Classifier In Code13m
5 lecturas
tjs-vis Documentation10m
MNIST Sprite Sheet10m
MNIST Classifier10m
Week 2 Wrap up10m
Exercise Description10m
1 ejercicio de práctica
Week 2 Quiz
Semana
3

Semana 3

5 horas para completar

Converting Models to JSON Format

5 horas para completar
12 videos (Total 28 minutos), 7 lecturas, 2 cuestionarios
12 videos
A Few Words From Laurence1m
Pre-trained TensorFlow.js Models49s
Toxicity Classifier3m
Toxicity Classifier In Code3m
MobileNet49s
Using MobileNet1m
Training Results1m
MobileNet Example In Code3m
Converting Models to JavaScript4m
Converting Models to JavaScript In Code2m
Linear Example In Code1m
7 lecturas
Important Links10m
Toxicity Classifier10m
Classes Supported by MobileNet10m
Image Classification Using MobileNet10m
Linear Model10m
Week 3 Wrap up10m
Optional - Install Wget (Only If Needed)10m
1 ejercicio de práctica
Week 3 Quiz
Semana
4

Semana 4

4 horas para completar

Transfer Learning with Pre-Trained Models

4 horas para completar
11 videos (Total 26 minutos), 3 lecturas, 2 cuestionarios
11 videos
A Few Words From Laurence53s
Building a Simple Web Page2m
Retraining the MobileNet Model1m
The Training Function2m
Capturing the Data3m
The Dataset Class2m
Training the Network with the Captured Data1m
Performing Inference4m
Rock Paper Scissors In Code4m
A Conversation with Andrew Ng1m
3 lecturas
Rock Paper Scissors10m
Exercise Description10m
Wrap up10m
1 ejercicio de práctica
Week 4 Quiz
4.7
39 revisionesChevron Right

Principales revisiones sobre Browser-based Models with TensorFlow.js

por ZBDec 20th 2019

Awesome - elegant in its complex simplicity. Clear explanations, logical curriculum structure, nice and knowledgeable code examples. A must-complete course indeed!

por SSJan 2nd 2020

Thanks to Laurence and Andrew for designing such a great course. I learnt a lot from this course and looking forward to learn more from both of you.

Acerca de Programa especializado 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 model. In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, use APIs to control how data splitting, and process all types of unstructured data. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more. Industries all around the world are adopting AI. This Specialization from Laurence Moroney and Andrew Ng will help you develop and deploy machine learning models across any device or platform faster and more accurately than ever. This Specialization builds upon skills learned in the TensorFlow in Practice Specialization. We recommend learners complete that Specialization prior to enrolling in TensorFlow: Data and Deployment....
TensorFlow: Data and Deployment

Preguntas Frecuentes

  • 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.

  • 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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