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.
Este curso forma parte de Programa Especializado - TensorFlow: Data and Deployment
Data Pipelines with TensorFlow Data Services
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Acerca de este Curso
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Qué aprenderás
Leverage built-in datasets with just a few lines of code
Use APIs to control how you split your data
Process all types of unstructured data
Habilidades que obtendrás
TensorflowMachine Learning
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 4 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
Aprox. 13 horas para completar
Sugerido: 4 weeks of study, 4-5 hours/week
Inglés (English)
Subtítulos: Inglés (English)
Programa - Qué aprenderás en este curso
5 horas para completar
Data Pipelines with TensorFlow Data Services
You'll learn about the types of data that you would normally come across when doing machine learning.
5 horas para completar
14 videos (Total 27 minutos), 2 lecturas, 2 cuestionarios
14 videos
Introduction1m
Popular datasets2m
Data pipelines58s
Extract, transform, load3m
Versioning datasets2m
Looking at the notebook1m
Introduction43s
Legacy API and Subsplits5m
Splits API (S3)2m
Introduction22s
Legacy API in code1m
Splits API (S3) in code1m
Week 1 wrap up43s
2 lecturas
Downloading the Coding Examples and Exercises10m
Try out the notebook yourself10m
1 ejercicio de práctica
Week 1 Quiz
6 horas para completar
Exporting your data into the training pipeline
This week you’re going to start looking at the code for using the data with input pipelines!
6 horas para completar
21 videos (Total 44 minutos), 5 lecturas, 2 cuestionarios
21 videos
Introduction22s
Input data1m
Basic mechanics2m
Numeric and bucketized columns2m
Vocabulary and hashed columns, feature crossing2m
Embedding columns2m
Introduction24s
Notebook walkthrough4m
Introduction19s
Numpy, Pandas and Images2m
CSV3m
Text and TFRecord1m
Generators1m
Introduction17s
Notebook walkthrough4m
Introduction1m
Numpy and Pandas2m
Images1m
CSV4m
Text2m
5 lecturas
Link to the notebook10m
Link to the CNN course10m
Link to the notebook10m
CSV: colab10m
Link to the tokenization10m
1 ejercicio de práctica
Week 2 Quiz
4 horas para completar
Performance
How you load your data into your model can have a huge impact on how efficiently the model trains. You'll learn how to handle your data input to avoid bottlenecks, race conditions and more!
4 horas para completar
11 videos (Total 20 minutos)
11 videos
Introduction36s
ETL2m
What happens when you train a model2m
Introduction25s
Caching58s
Parallelism APIs2m
Autotuning2m
Parallelizing data extraction2m
Best practices for code improvements3m
A few words by Laurence34s
1 ejercicio de práctica
Week 3 Quiz
5 horas para completar
Publishing your datasets
This week let’s learn about how you can share your data with the world in a way that’s easy for others to consume!
5 horas para completar
11 videos (Total 24 minutos), 2 lecturas, 2 cuestionarios
11 videos
Introduction44s
How to start using a dataset2m
Implementation4m
File access and possible problems in data3m
Publishing the dataset3m
Introduction18s
Going through the colab (1)2m
Going through the colab (2)2m
Closing words14s
A conversation with Andrew Ng1m
2 lecturas
URLs10m
Link to the colab10m
1 ejercicio de práctica
Week 4 Quiz
Revisiones
Principales revisiones sobre DATA PIPELINES WITH TENSORFLOW DATA SERVICES
por GLMar 2, 2020
Laurence cares deeply about the students. Not only about what they learn, but that they actually enjoy and learn it. What a fantastic teacher.
por NBMar 29, 2020
This seemed very helpful and hands on. I can't wait to try this on my own.
por ADFeb 2, 2020
Excellent course both for Data Scientists and Machine Learning Engineers!
Acerca de deeplearning.ai
deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders.
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 machine learning models.
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, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy. 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 Artificial Intelligence. 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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
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.
¿Qué recibiré si me suscribo a este Programa especializado?
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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