Machine Learning on Google Cloud Platform
Learning Path Description
This learning path will introduce you to neural networks, TensorFlow, and Google Cloud Machine Learning Engine. Even if you don't have any previous experience with machine learning, that's okay, because these courses cover the basic concepts.
The first course explains the fundamentals of neural networks and how to implement them using TensorFlow. Then it shows you how to train and deploy a model using Cloud ML Engine.
The second course explains how to build convolutional neural networks, which are very effective at performing object detection in images, among other tasks. It also shows how to visualize a model's performance using TensorBoard, reduce overfitting, and train a model on a custom cluster using Cloud ML Engine.
Both of these courses include hands-on demos you can do yourself. Then you can test what you’ve learned by taking the exam.
- Describe how an artificial neural network functions
- Run a simple TensorFlow program
- Train a model using a distributed cluster on Cloud ML Engine
- Increase prediction accuracy using feature engineering and both wide and deep networks
- Deploy a trained model on Cloud ML Engine to make predictions with new data
- Build a Convolutional Neural Network in TensorFlow
- Analyze a model’s training performance using TensorBoard
- Identify cases of overfitting and apply techniques to prevent it
- Scale a Cloud ML Engine job using a custom configuration
- Data professionals
- Google Cloud Platform account recommended (sign up for free trial at https://cloud.google.com/free if you don’t have an account)
This Learning Path Includes
- 2 video courses
- 1 exam
If you have thoughts or suggestions for this learning path, please contact Cloud Academy at email@example.com.