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.

Learning Objectives

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
Intended Audience
Data professionals
Prerequisites
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

Miscellaneous
Provider: Cloud Academy
Title: Machine Learning on Google Cloud Platform

Knowledge must be free. We are a 0day e-learning release group.
You can find us on Discord and pass some exams together. You will know when you found us.

Internal ID: CA206

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