Inside TensorFlow

Learners: 1

Instructor: /

Duration: 17.00

Explore the heart of the open-source AI framework that's shaping the future of machine learning and artificial intelligence. #InsideTensorFlow #AI #TensorFlow #Tech ▼▲

Course Feature Course Overview Course Provider Discussion and Reviews

Go to class

Course Feature

Cost:

Free

Provider:

Youtube

Certificate:

Paid Certification

Language:

English

Start Date:

On-Demand

Course Overview

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

Updated in [August 31st, 2023]

What does this course tell?
(Please note that the following overview content is from Alison)
Inside TensorFlow: New TF Lite ConverterInside TenseFlow: Quantization aware training inside Tensorflow: Parameter server training Inside Tensor Flow: MLIR for TF developers inside TF-Agents inside tensorflowdata - TF Input Pipeline

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?
This course will provide learners with the skills and knowledge to use TensorFlow for machine learning applications. Learners will gain an understanding of the TF Lite Converter, Quantization aware training, Parameter server training, MLIR for TF developers, TF-Agents, and the TensorFlow Input Pipeline. They will also learn how to use these tools to create and deploy machine learning models.
lHow does this course contribute to professional growth?
This course contributes to professional growth by providing an in-depth understanding of the TensorFlow framework. It covers topics such as the new TF Lite Converter, Quantization aware training, Parameter server training, MLIR for TF developers, TF-Agents, and the TF Input Pipeline. By understanding these topics, professionals can gain the skills necessary to develop and deploy machine learning models using TensorFlow. This course also provides an opportunity to gain hands-on experience with the TensorFlow framework, which can help professionals to become more proficient in their work.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education. It covers topics such as TF Lite Converter, Quantization aware training, Parameter server training, MLIR for TF developers, TF-Agents, and TF Input Pipeline. All of these topics are essential for further education in the field of TensorFlow.