Applied Machine Learning with BigQuery on Google Cloud

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Mike West

2:28:13

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01.01-introduction.mp4

02:37

01.02-section introduction.mp4

02:30

01.03-scaling out instead of up.mp4

01:33

01.04-googles scaled out revolution.mp4

04:06

01.05-demo creating an account on googles cloud platform.mp4

04:23

02.01-section introduction.mp4

01:58

02.02-bigquery defined.mp4

02:07

02.03-bigquery stores structured data.mp4

01:47

02.04-parallel execution.mp4

01:17

02.05-demo web ui.mp4

01:29

02.06-what bigquery is not.mp4

01:58

02.07-bigquery technology stack.mp4

02:31

02.08-demo navigation basics.mp4

05:00

03.01-section introduction.mp4

01:25

03.02-three core careers.mp4

03:11

03.03-applied machine learning.mp4

03:59

03.04-the machine learning process.mp4

02:14

03.05-types of machine learning.mp4

03:14

03.06-why python is king.mp4

01:30

03.07-install python on windows.mp4

01:27

03.08-install python on a mac.mp4

09:28

03.09-array.mp4

01:31

03.10-basic jupyter notebook navigation.mp4

05:49

04.01-section overview.mp4

01:44

04.02-core machine learning libraries.mp4

02:20

04.03-demo core machine learning libraries.mp4

07:15

04.04-sourcing data.mp4

04:32

04.05-exploratory data analysis.mp4

04:40

04.06-data cleansing.mp4

02:37

04.07-demo modeling.mp4

03:28

05.01-section introduction.mp4

01:38

05.02-linear regression.mp4

01:56

05.03-demo linear regression.mp4

02:27

05.04-classification.mp4

01:18

05.05-demo classification.mp4

03:38

05.06-what is an artificial neural network.mp4

03:24

06.01-section introduction.mp4

02:25

06.02-datasets and tables.mp4

03:10

06.03-demo datasets and tables.mp4

01:56

06.04-demo cloud datalab.mp4

02:58

06.05-demo modeling the titanic dataset in cloud datalab.mp4

03:04

06.06-demo modeling the iris dataset on cloud datalab.mp4

05:42

06.07-demo scale cloud datalab.mp4

02:06

06.08-bigquery ml.mp4

01:33

06.09-demo bigquery ml binary logistic regression.mp4

03:33

06.10-installing the google cloud sdk.mp4

03:07

06.11-demo gsutil navigation basics.mp4

04:21

06.12-demo segmenting datasets.mp4

06:17

9781803244389 Code.zip

Description

Right now, applied machine learning is one of the most in-demand career fields in the world, and will continue to be for some time. Most of the applied machine learning is supervised. That means models are built against existing datasets.

Most real-world machine learning models are built in the cloud or on large on-premises boxes. In the real world, we don’t build models on laptops or on desktop computers.

Google Cloud Platform’s BigQuery is a serverless, petabyte-scale data warehouse designed to house structured datasets and enable lightning-fast SQL queries. Data scientists and machine learning engineers can easily move their large datasets to BigQuery without having to worry about scale or administration, so you can focus on the tasks that really matter—generating powerful analysis and insights.

This course covers the basics of applied machine learning and an introduction to BigQuery ML. You will also learn how to build your own machine learning models at scale using BigQuery.

By the end of this course, you will be able to harness the benefits of GCP’s fully managed data warehousing service.

All resources to this course are placed here: https://github.com/PacktPublishing/Applied-Machine-Learning-with-BigQuery-on-Google-s-Cloud

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Machine Learning

Google Cloud

Mike West

Instructor's Courses

Mike has Bachelor of Science degrees in Business and Psychology. He started his career as a middle school psychologist prior to moving into the information technology space. His love of computers resulted in him spending many additional hours working on computers while studying for his master's degree in Statistics. His current areas of interests include Machine Learning, Data Engineering and SQL Server. When not working, Mike enjoys spending time with his family and traveling.

PacktPub

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.