Este curso forma parte de Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

4.7
estrellas
18,170 calificaciones

96 %

Laurence Moroney

318.635 ya inscrito

Ofrecido Por

Certificado profesional de DeepLearning.AI desarrollador de TensorFlowdeeplearning.ai

Acerca de este Curso

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If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. 
The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

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Certificado para compartir

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Curso 1 de 4 en

Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

Nivel intermedio

Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.

Aprox. 18 horas para completar

Inglés (English)

Qué aprenderás

Learn best practices for using TensorFlow, a popular open-source machine learning framework
Build a basic neural network in TensorFlow
Train a neural network for a computer vision application
Understand how to use convolutions to improve your neural network

Habilidades que obtendrás

Computer Vision
Tensorflow
Machine Learning

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 1 de 4 en

Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

Nivel intermedio

Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.

Aprox. 18 horas para completar

Inglés (English)

Instructor

Calificación del instructor

4,82/5 (4576 calificaciones)

Laurence Moroney

Instructor

Lead AI Advocate, Google

408.232 alumnos

15 cursos

Ofrecido por

deeplearning.ai

Programa - Qué aprenderás en este curso

Calificación del contenido96%(41,649 calificaciones)

Semana

Semana 1

3 horas para completar

A New Programming Paradigm

Welcome to this course on going from Basics to Mastery of TensorFlow. We're excited you're here! In Week 1, you'll get a soft introduction to what Machine Learning and Deep Learning are, and how they offer you a new programming paradigm, giving you a new set of tools to open previously unexplored scenarios. All you need to know is some very basic programming skills, and you'll pick the rest up as you go along. To get started, check out the first video, a conversation between Andrew and Laurence that sets the theme for what you'll study...

3 horas para completar

4 videos (Total 16 minutos), 7 lecturas, 5 cuestionarios

4 videos

Introduction: A conversation with Andrew Ng3m

A primer in machine learning3m

The ‘Hello World’ of neural networks5m

Working through ‘Hello World’ in TensorFlow and Python3m

7 lecturas

Where to find the notebooks for this course5m

From rules to data2m

FAQs about Google Colab (optional)10m

Try it for yourself (Lab 1)20m

Assignment Troubleshooting Tips5m

(Optional) Downloading your Notebook and Refreshing your Workspace5m

Week 1 Resources10m

1 ejercicio de práctica

Week 1 Quiz30m

Semana

Semana 2

5 horas para completar

Introduction to Computer Vision

5 horas para completar

7 videos (Total 15 minutos), 5 lecturas, 3 cuestionarios

7 videos

A Conversation with Andrew Ng2m

An Introduction to computer vision2m

Writing code to load training data2m

Coding a Computer Vision Neural Network2m

Walk through a Notebook for computer vision3m

Using Callbacks to control training1m

Walk through a notebook with Callbacks1m

5 lecturas

Exploring how to use data10m

The structure of Fashion MNIST data1m

See how it's done

Get hands-on with computer vision (Lab 1)1h

See how to implement Callbacks (Lab 2)30m

1 ejercicio de práctica

Week 2 Quiz30m

Semana

Semana 3

5 horas para completar

Enhancing Vision with Convolutional Neural Networks

5 horas para completar

6 videos (Total 19 minutos), 5 lecturas, 3 cuestionarios

6 videos

A conversation with Andrew Ng1m

What are convolutions and pooling?2m

Implementing convolutional layers1m

Implementing pooling layers4m

Improving the Fashion classifier with convolutions5m

Walking through convolutions3m

5 lecturas

Coding convolutions and pooling layers10m

Learn more about convolutions1m

Getting hands-on, your first ConvNet

Try it for yourself (Lab 1)1h

Experiment with filters and pools (Lab 2)1h

1 ejercicio de práctica

Week 3 Quiz30m

Semana

Semana 4

5 horas para completar

Using Real-world Images

5 horas para completar

9 videos (Total 27 minutos), 10 lecturas, 3 cuestionarios

9 videos

A conversation with Andrew Ng2m

Understanding ImageDataGenerator4m

Defining a ConvNet to use complex images2m

Training the ConvNet2m

Walking through developing a ConvNet2m

Walking through training the ConvNet3m

Adding automatic validation to test accuracy4m

Exploring the impact of compressing images3m

A conversation with Andrew1m

10 lecturas

Explore an impactful, real-world solution3m

Designing the neural network

Train the ConvNet with ImageDataGenerator

Exploring the solution

Training the neural network10m

Experiment with the horse or human classifier (Lab 1)1h

Get hands-on and use validation (Lab 2)30m

Get Hands-on with compacted images (Lab 3)30m

Wrap up

Acknowledgments5m

1 ejercicio de práctica

Week 4 Quiz30m

Reseñas

4.7

3772 reseña

5 stars
80,61 %
4 stars
15,63 %
3 stars
2,49 %
2 stars
0,64 %
1 star
0,61 %

Principales reseñas sobre INTRODUCTION TO TENSORFLOW FOR ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AND DEEP LEARNING

por AS8 de mar. de 2019

Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?

por JL5 de abr. de 2020

It's a good hands-on exercise. I like to see more link to keras api document when we introduce new function in keras. However, Tensorflow document regarding keras api is yet in complete. Thank you.

por EL13 de nov. de 2022

The instructor was beneficial in delivering the course in a byte-sized format. Furthermore, the problem-based approach was a bonus, because I feel like earning the certificate was definitely worth it

por SG11 de jun. de 2019

Es un excelente curso para todo aquel que este interesado en las ciencias de datos y la inteligencia artificial ya que Tensorflow y Keras son herrameintas que acortan mucho el camino de desarrollo.

Ver todas las reseñas

Acerca de Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.

In this hands-on, four-course Professional Certificate program, you’ll learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. This program can help you prepare for the Google TensorFlow Certificate exam and bring you one step closer to achieving the Google TensorFlow Certificate. Ready to deploy your models to the world? Learn how to go live with your models with the TensorFlow: Data and Deployment Specialization. Looking to customize and build powerful real-world models for complex scenarios? Check out the TensorFlow: Advanced Techniques Specialization.

DeepLearning.AI desarrollador de TensorFlow

Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Certificado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos del Certificado 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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Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Acerca de este Curso

Qué aprenderás

Habilidades que obtendrás