Google Cloud Machine Learning with TensorFlow, published by Packt publishing This is the code repository for Google Cloud Machine Learning with TensorFlow, published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
TensorFlow has become the first choice for deep learning tasks because of the way it facilitates building powerful and sophisticated neural networks. The Google Cloud Platform is a great place to run TF models at scale, and perform distributed training and prediction.
This course shows you how to use Google Cloud to train TensorFlow models and use them to predict results for multiple users. You will learn to efficiently train neural networks using large datasets and to serve your training models.
With this video course, you will use the power of Google's Cloud Platform to train deep neural networks faster. This course supplies various examples of training in Google Cloud AI Platform. You will also learn to run predictions for your model using the cloud. You will explore topics such as cloud infrastructures, distributed training, serverless technologies, model serving, and more.
By the end of the course, you will be expert at training and serving neural models, and beyond.
- Get access to powerful computers with GPUs organized in clusters to optimize your performance functions
- Train bigger models faster using the Google Cloud infrastructure
- Explore machine types and learn how to configure clusters to solve problems
- Train deep learning models using the Google Cloud AI Platform
- Run classical machine learning algorithms with TensorFlow
- Run your trained models to get predictions using the AI Platform API
This course targets data scientists, people starting their journey in the ML/DL domain, and anyone keen to start training deep neural networks using cloud infrastructures. Familiarity with ML concepts will be advantageous.
-
Minimum Hardware Requirements
- OS: Windows 7+ / MacOS El Capitan / Ubuntu / Debian
- Connectivity: Working internet connection is required
- Processor: Intel core I5 or equivalent
- Memory: 4GB - 16GB RAM
- Storage: 20GB
-
Software Requirements
- OS: Windows 7+ / MacOS El Capitan / Ubuntu / Debian
- Browser: Any popular browser
- Atom IDE, Latest Version, https://atom.io/