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Predicting Taxi fares in NYC using Google Cloud AI Platform (Billion + rows) Par...
source link: https://www.tuicool.com/articles/NzIjmu3
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In this series of articles, we are working on a real-world dataset of taxi rides in NYC which is hosted in BigQuery to be able to estimate the fare amount.
In theprevious post, we set up a project on the Google Cloud Platform, started an AI notebook instance with TensorFlow pre-installed, and prepared/cleaned/sampled the data. Now comes the part where we build a model to predict the target variable.
We are going to use tf.estimator , a high-level TensorFlow API to build our models. Detailed information can be found here .
There are four major steps to use this API.
- Create a function to import the dataset
- Define the feature columns
- Instantiate the Estimator
- Train/Evaluate
Create a function to import the dataset
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