Applied Machine Learning With Bigquery On Google'S Cloud
Last updated 7/2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 639.89 MB | Duration: 2h 25m
Last updated 7/2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 639.89 MB | Duration: 2h 25m
Building Machine Learning Models at Scale
What you'll learn
You'll receive an introduction to BigQuery specific to machine learning
You Learn the Basics of the Google Cloud Platform, specific to BigQuery
You'll learn the basics of applied machine learning from a machine learning engineer
Learn how to building your own machine learning models at scale using BigQuery
Requirements
You should have a basic knowledge of SQL
You should have basic knowledge of machine learning
Description
Welcome to Applied Machine Learning with BigQuery on Google's Cloud.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 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-prem boxes. In the real-world, we don't built 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.In this course, you’ll:Get an introduction to BigQuery ML.Get a good introductory grounding in Google Cloud Platform, specific to BigQuery.Learn the basics of applied machine learning.Understand the history, architecture and use cases of BigQuery for machine learning engineers.Learn how to building your own machine learning models at scale using BigQuery.This is a mid-level course and basic experience with SQL and Python will help you get the most out of this course.So what are you waiting for? Get hands-on with BigQuery and harness the benefits of GCP's fully managed data warehousing service.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Section Introduction
Lecture 3 Scaling Out Instead of Up
Lecture 4 Google's Scaled Out Revolution
Lecture 5 Demo: Creating an Account on Google's Cloud Platform
Section 2: BigQuery Basics
Lecture 6 Section Introduction
Lecture 7 BigQuery Defined
Lecture 8 BigQuery Stores Structured Data
Lecture 9 Parallel Execution
Lecture 10 Demo: Web UI
Lecture 11 What BigQuery Is Not
Lecture 12 BigQuery Technology Stack
Lecture 13 Demo: Navigation Basics
Section 3: An Introduction to Applied Machine Learning
Lecture 14 Section Introduction
Lecture 15 Three Core Careers
Lecture 16 Applied Machine Learning
Lecture 17 The Machine Learning Process
Lecture 18 Types of Machine Learning
Lecture 19 Why Python is King
Lecture 20 Install Python on Windows
Lecture 21 Install Python on a MAC
Lecture 22 The Array
Lecture 23 Basic Jupyter Notebook Navigation
Section 4: Machine Learning Libraries
Lecture 24 Section Overview
Lecture 25 Core Machine Learning Libraries
Lecture 26 Demo: Core Machine Learning Libraries
Lecture 27 Sourcing Data
Lecture 28 Exploratory Data Analysis
Lecture 29 Data Cleansing
Lecture 30 Demo: Modeling
Section 5: Classification and Regression
Lecture 31 Section Introduction
Lecture 32 Linear Regression
Lecture 33 Demo: Linear Regression
Lecture 34 Classification
Lecture 35 Demo: Classification
Lecture 36 What is an Artificial Neural Network?
Section 6: Machine Learning with BigQuery
Lecture 37 Section Introduction
Lecture 38 Datasets and Tables
Lecture 39 Demo: Datasets and Tables
Lecture 40 Demo: Cloud Datalab
Lecture 41 Demo: Modeling the Titanic Dataset in Cloud Datalab
Lecture 42 Demo: Modeling the Iris Dataset on Cloud Datalab
Lecture 43 Demo: Scale Cloud Datalab
Lecture 44 BigQuery ML
Lecture 45 Demo: BigQuery ML Binary Logistic Regression
Lecture 46 Installing the Google Cloud SDK
Lecture 47 Demo: gsutil Navigation Basics
Lecture 48 Demo: Segmenting Datasets
If you're interested in learning how to build real-world models at scale, this course is for you,If you want to learn the most used service on GCP, this course is for you,If you want to learn why so many machine learning engineers use BigQuery, this course is for you