- Model Interpretability
- Object Detection
- Custom and Exotic Models
- Generative Machine Learning
- Custom Training Loops
TensorFlow: Advanced Techniques
Completed by Yoshihisa Nitta
August 31, 2022
Approximately 2 months at 10 hours a week to completeYoshihisa Nitta's account is verified. Coursera certifies their successful completion of DeepLearning.AI TensorFlow: Advanced Techniques Specialization.
Course Certificates Completed
Custom Models, Layers, and Loss Functions with TensorFlow
Custom and Distributed Training with TensorFlow
Advanced Computer Vision with TensorFlow
Generative Deep Learning with TensorFlow
What you will learn
Understand the underlying basis of the Functional API and build exotic non-sequential model types, custom loss functions, and layers.
Learn optimization and how to use GradientTape & Autograph, optimize training in different environments with multiple processors and chip types.
Practice object detection, image segmentation, and visual interpretation of convolutions.
Explore generative deep learning, and how AIs can create new content, from Style Transfer through Auto Encoding and VAEs to GANs.
Skills you will gain
Course Certificates
Earned after completing each course in the Specialization
Custom Models, Layers, and Loss Functions with TensorFlow
DeepLearning.AI
Taught by: Laurence Moroney & Eddy Shyu
Completed by: Yoshihisa Nitta by August 2, 2022
At the rate of 5 hours a week, it typically takes 4 weeks to complete this course.
Custom and Distributed Training with TensorFlow
DeepLearning.AI
Taught by: Laurence Moroney & Eddy Shyu
Completed by: Yoshihisa Nitta by August 16, 2022
At the rate of 5 hours a week, it typically takes 4 weeks to complete this course.
Advanced Computer Vision with TensorFlow
DeepLearning.AI
Taught by: Laurence Moroney & Eddy Shyu
Completed by: Yoshihisa Nitta by August 26, 2022
At the rate of 5 hours a week, it typically takes 4 weeks to complete this course.
Generative Deep Learning with TensorFlow
DeepLearning.AI
Taught by: Laurence Moroney & Eddy Shyu
Completed by: Yoshihisa Nitta by August 31, 2022
At the rate of 5 hours a week, it typically takes 4 weeks to complete this course.