explanation
TensorFlow: Advanced Technology Specialization This is a TensorFlow library training course. TensorFlow is an open source machine learning platform with a complete and flexible ecosystem of tools and libraries. Using TensorFlow and more, researchers can gain access to the latest achievements in machine learning, and developers can immediately take advantage of the power of machine learning to perform well-equipped tasks. The main applications of TensorFlow are applications such as speech recognition, Google Translate, image recognition, and natural language processing. This course is for all software engineers and machine learning users who have a basic understanding of TensorFlow and want to expand their knowledge and skills by learning advanced features of TensorFlow.
The course is divided into four sub-periods, during which you will gain practical and practical knowledge of TensorFlow. In the first part, we will understand the basic functional principles of the API and build out-of-order models, personalized loss functions, and various layers. In the second part, we’ll walk you through how to do optimization functions, get familiar with using GradientTape and Steve, and train with different environments and a number of improvements to chip processors and prompts. In the third part, you will learn advanced insights about computers, such as what to detect, and practice scenarios. Visual interpretation of sliced images and distortions, and the fourth part explores how to use hash dildos for deep learning, productivity, and new content creation. Dedicated to encryption, automation, VAE, and GAN.
What do you learn?
Understand the basic functional fundamentals of the API and build strange out-of-order model loss functions and layers.
Learn optimization in different situations and use GradientTape and Autograph.
Practice visual interpretation of object recognition, image fragmentation, and torsion.
From transition styles to algorithms, ventilator-related events or VAEs and networks, to generative adversarial networks or GANs, explore deep learning from manufacturers for building new content.
What skills do you acquire?
Model commentary
Training rings, loss functions and custom layers
distribution strategy
Build personal, sophisticated models using functional APIs.
Optimize using gradient tape
and…
TensorFlow Specification: Advanced Technology Specialization
Publisher: Coursera
Instructors: Lawrence Moroney, Eddie Shu
Language:English
Training level: Intermediate
Quantity: 4 courses
Course Duration: The suggested duration is 6 hours per week, approximately 5 months.
procedure
- Custom models, layers, and loss functions using TensorFlow
- Custom and distributed training with TensorFlow
- Advanced computer vision with TensorFlow
- Generative Deep Learning with TensorFlow
precondition
- Learners must have working knowledge of AI and deep learning. You should have intermediate Python skills (understanding decorators and context managers preferred) and experience with deep learning frameworks (TensorFlow, Keras, or PyTorch). Learners should be proficient in basic calculus, linear algebra, and statistics.
- We recommend that you complete the following: Deep Learning Specialization Before starting this specialization.
image
sample video
installation manual
Custom view after extraction to player.
Subtitles: English
Quality: 720p
download link
Password file: free download software
file size
1.35 GB