BigQuery ML – Machine Learning in SQL using Google BigQuery

BigQuery ML lets you create and execute machine learning models in BigQuery using standard SQL queries.

Big Query ML is a blessing for engineers who want to work in Machine Learning domain but lack programming language like Python, R. With Big Query ML, they can use their existing SQL knowledge to build operational production–grade Machine learning models.

What’s included in the course ?

Brief introduction to various Machine Learning services of Google Cloud.

Fundamentals of BigQuery ML and challenges which it solves.

All of the Machine Learning algorithms are explained in 2 Steps :

Step 1 : Theoretical explanation of working of an ML algorithm.

Step 2 : Practical implementation of the ML algorithm in BigQuery ML.

Each and every Machine learning algorithm is explained with HANDS–ON examples.

Hyperparameter tuning of models, Model Explainability functions, Feature pre–processing functions.

Model management operations using bq commands.

BigQuery ML pricing (Flat rate & On–demand pricing models).

Assignment for each Machine learning algorithm for self Hands–On in Big Query ML.

Learn Best practices and Optimization techniques for BigQuery ML.

Machine Learning algorithms explained:

Linear regression

Logistic regression

K–means clustering

Boosted Tree

Deep neural networks

ARIMA+ Time series Forecasting

Product Component Analysis (PCA)

Matrix Factorization

After completing this course, you can confidently start creating production–grade Machine Learning models in Real–world corporate projects using BigQuery ML.