TensorFlow Hub: Deep Learning Computer Vision and NLP faq

star-rating
4.7
learnersLearners: 701
instructor Instructor: Jones GranatyrAI Expert Academy instructor-icon
duration Duration: duration-icon

Unleash the power of TensorFlow Hub for Computer Vision and NLP! Explore pre-trained models and streamline your deep learning projects with ease. #TensorFlowHub #ComputerVision #NLP #AIInstitute

ADVERTISEMENT

Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Paid

providerProvider:

Udemy

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

2023-04-27

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [August 31st, 2023]

We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
In this course, students will acquire skills and knowledge in the areas of deep learning, computer vision, and natural language processing. They will learn how to use Google TensorFlow and TensorFlow Hub to build complex solutions for business problems. They will gain practical experience in the implementation of projects such as classification of five species of flowers, detection of over 80 different objects, creating new images using style transfer, using GANs to complete missing parts of images, recognition of actions in videos, text polarity classification, and using a question and answer dataset to find similar documents. They will also learn how to use Google Colab online to implement all of these projects step by step.
lHow does this course contribute to professional growth?
This course contributes to professional growth by providing a practical overview of some of the main TensorFlow Hub models that can be applied to the development of Deep Learning projects. Through the course, participants will gain the necessary tools to use TensorFlow Hub to build complex solutions that can be applied to business problems. Participants will also have the opportunity to implement projects such as classification of five species of flowers, detection of over 80 different objects, creating new images using style transfer, recognition of actions in videos, text polarity classification, and audio classification. By the end of the course, participants will have a better understanding of how to use TensorFlow Hub to develop Deep Learning projects.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education as it provides a practical overview of some of the main TensorFlow Hub models that can be applied to the development of Deep Learning projects. It covers topics such as classification of five species of flowers, detection of over 80 different objects, creating new images using style transfer, recognition of actions in videos, text polarity classification, and audio classification. The course also provides more than 50 classes and more than 7 hours of videos, which can help students gain a better understanding of the concepts and techniques used in Deep Learning.

Course Syllabus

Introduction

Computer vision

Natural language processing

Extra content 1: Artificial neural networks

Extra content 2: Convolutional neural networks

Final remarks

Course Provider

Provider Udemy's Stats at AZClass

Discussion and Reviews

0.0   (Based on 0 reviews)

Start your review of TensorFlow Hub: Deep Learning Computer Vision and NLP

faq FAQ for Tensorflow Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a paid certificate. AZ Class have already checked the course certification options for you. Access the class for more details.

Q2: How do I contact your customer support team for more information?

If you have questions about the course content or need help, you can contact us through "Contact Us" at the bottom of the page.

Q3: How many people have enrolled in this course?

So far, a total of 701 people have participated in this course. The duration of this course is hour(s). Please arrange it according to your own time.

Q4: How Do I Enroll in This Course?

Click the"Go to class" button, then you will arrive at the course detail page.
Watch the video preview to understand the course content.
(Please note that the following steps should be performed on Udemy's official site.)
Find the course description and syllabus for detailed information.
Explore teacher profiles and student reviews.
Add your desired course to your cart.
If you don't have an account yet, sign up while in the cart, and you can start the course immediately.
Once in the cart, select the course you want and click "Enroll."
Udemy may offer a Personal Plan subscription option as well. If the course is part of a subscription, you'll find the option to enroll in the subscription on the course landing page.
If you're looking for additional Tensorflow courses and certifications, our extensive collection at azclass.net will help you.

close

To provide you with the best possible user experience, we use cookies. By clicking 'accept', you consent to the use of cookies in accordance with our Privacy Policy.