Customising your models with TensorFlow 2 faq

learnersLearners: 134
instructor Instructor: Dr Kevin Webster instructor-icon
duration Duration: duration-icon

TensorFlow 2 makes customising your models easier than ever before, with its intuitive and powerful tools that guarantee results - and this online course will show you how!

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

Course Feature

costCost:

Free

providerProvider:

Coursera

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

29th May, 2023

Course Overview

❗The content presented here is sourced directly from Coursera 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?
By taking this course, students will acquire the skills and knowledge to develop fully customised deep learning models and workflows for any application. They will learn to use lower level APIs in TensorFlow to develop complex model architectures, customised layers and a flexible data workflow. They will also expand their knowledge of the TensorFlow APIs to include sequence models. Students will gain practical experience by putting concepts into practice in hands-on coding tutorials and programming assignments. At the end of the course, students will bring many of the concepts together in a Capstone Project where they will develop a custom neural translation model from scratch. The prerequisite knowledge required for this course is proficiency in the Python programming language (this course uses Python 3), knowledge of general machine learning concepts (such as overfitting & underfitting, supervised learning tasks, validation, regularisation and model selection) and a working knowledge of the field of deep learning including typical model architectures (MLP, CNN, RNN, ResNet) and concepts such as transfer learning, data augmentation and word embeddings.
lHow does this course contribute to professional growth?
This course on Customising your models with TensorFlow 2 provides an opportunity for professional growth. It allows learners to deepen their knowledge and skills with TensorFlow in order to develop fully customised deep learning models and workflows for any application. Through practical hands-on coding tutorials and a series of automatically graded programming assignments, learners will be able to put concepts that they learn about into practice and consolidate their skills. At the end of the course, learners will be able to develop a custom neural translation model from scratch. This course is a great opportunity for professionals to expand their knowledge of the TensorFlow APIs and gain a better understanding of the open source machine library.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education as it provides a comprehensive overview of TensorFlow 2 and its capabilities. It covers topics such as lower level APIs, complex model architectures, sequence models, practical coding tutorials, programming assignments, and a Capstone Project. It also requires prerequisite knowledge in Python programming, machine learning concepts, and deep learning.

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faq FAQ for Tensorflow Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a free 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: Can I take this course for free?

Yes, this is a free course offered by Coursera, please click the "go to class" button to access more details.

Q4: How many people have enrolled in this course?

So far, a total of 134 people have participated in this course. The duration of this course is hour(s). Please arrange it according to your own time.

Q5: 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 Coursera'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."
Coursera 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.

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