Review GPUs and TPUs for use in optimizing custom machine learning models built using TensorFlow. Learn how to use a notebook to test performance differences in the same custom model when run on a CPU vs. a GPU.
- [Instructor] So, as we're learning about…working with deep neural networks…for machine learning,…we need to consider a type of hardware…that is sometimes used with deep neural networks,…particularly TensorFlow,…and that's called a GPU.…So, a GPU is a graphics processing unit.…It's not a new type of hardware,…it's been used for a really long time…to optimize the display of video for high end laptops.…For example for, they called gaming laptops…where you have a intense video display.…
What's interesting about this in relation to…deep neural networks is the fact that TensorFlow…is optimized to offload some of…the model training processing to these GPUs…which are becoming more and more regularly available…as part of the hardware on both laptops and servers.…So to summarize GPUs and CPUs…as they relate to deep neural networks,…CPUs are made with few complex cores.…GPUs are hundreds of simpler cores.…
CPUs are made for single thread performance optimization.…GPUs are thousands of concurrent hardware threads.…CPUs are transistor space dedicated to complex ILP…
- Hosting options: Serverless, containers, and virtual machines
- Enabling the GCP ML AIs
- Preparing data with Cloud Dataflow and Dataprep
- Modeling predictions for images, video, text to speech, and cloud translation
- Machine learning with AutoML
- Advanced machine learning and deep learning
- Machine learning architectures
Skill Level Intermediate
1. Machine Learning on Google Cloud Platform
2. Machine Learning API Services
3. Machine Learning with AutoML
Understand AutoML Vision4m 57s
4. Advanced Machine Learning
5. Machine Learning Architectures
Next steps1m 30s
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