| Model type | Custom deep learning model | BigQuery ML | AutoML |
|---|---|---|---|
| How | Keras with a TensorFlow backend, trained on Cloud ML Engine | SQL in BigQuery for ML on structured data | AutoML uses neural architecture search and best-of-class model architectures for the specific problem |
| Best if you are a | ML Engineer who knows Python and knows NLP techniques | Data analyst who can wrangle data with SQL | Developer who can create the dataset in the required format |
| How long it takes an experienced practioner | A week to a month | About an hour | About a day |
| Most of this time is spent in | Coding Python and experimentation with ML | Writing SQL | Waiting for job to finish |
| Cloud computing costs | Medium to high depending on size of data, number of experiments, etc. | Low | Medium |
| Accuracy | Low if you don't know what you are doing; extremely high if you employ appropriate architectures and have a large-enough dataset | Moderate to high, mostly depending on the size of your dataset | High |
| Suggested way to learn | Coursera specialization: Advanced Machine Learning with TensorFlow | Coursera course: Applying ML to your data | Quickstart for AutoML Natural Language, Vision, Translate etc. |
Last active
February 21, 2020 05:56
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