From the course: Building and Deploying Deep Learning Applications with TensorFlow
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The train/test/evaluation flow in TensorFlow - TensorFlow Tutorial
From the course: Building and Deploying Deep Learning Applications with TensorFlow
The train/test/evaluation flow in TensorFlow
- [Instructor] In this course, we'll be using TensorFlow to build and deploy a supervised machine learning model. Supervised machine learning is the branch of machine learning where we train the model by showing it input data and the expected result for that data. And it works out how to transform the input into the output. When building and using a supervised machine learning model, there's a process we always follow called the model of train, test, evaluation flow. First, we'll need to choose which machine learning algorithm we want to use to build our model. We can pick any standard machine learning algorithm but in this course we'll be using neural networks. Then we can start with the train phase. We train the algorithm by showing it training data and the expected output for that data and it has to figure out how to come up with the expected result. In other words, the algorithm learns how to transform the input to produce the correct output. For example, we can train it to do…
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