MACHINE LEARNING IN PPC How To Get Started Today · 2019-02-13 · Our Agenda: Intro & 3 PPC Use...
Transcript of MACHINE LEARNING IN PPC How To Get Started Today · 2019-02-13 · Our Agenda: Intro & 3 PPC Use...
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MACHINE LEARNING IN PPC
How To Get Started TodayChristopher Gutknecht | norisk Group | #FOS19
#FOS19
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Our Agenda: Intro & 3 PPC Use Cases
Query Understanding
Text Summarization
Prediction 2. Analysing Query n-Grams
3. Finding Key Phrases
INTRO Machine Learning Essentials
1. Classifying Near-Exact
ML Toolkit For PPC Platforms & Tools
#FOS19
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Note: I’m not a Data Scientist - I’m a PPC
Machine Learning
Javascript
Python
2008 2014 2016
PPC Automation
PPC
20182012
Christopher GutknechtHead of Online Marketing @ norisk
Munich-basedFocus Ecom & RetailSelf Taught DevDad of 2,5 yr old
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Think of Me As a Knowledgeable Tourist
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
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Let’s Get Started with ML Essentials
INTRO Machine Learning Essentials
#FOS19
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What Do We All Have in Common?
DATA
DATA EVERYWHERE
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Data-Driven Nature Makes ML Relevant
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“ML-Worthy” PPC Automation Tasks
● Keyphrase extraction● Text summarization● ...
Query Understanding
● Typo Detection● Entity recognition● ...
Monitoring Text Generation
● Anomaly detection● Semantic inventory match● ...
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Let’s Get To Know our ML Starter Toolkit
INTRO Machine Learning Essentials
ML Toolkit For PPC Platforms & Tools
#FOS19
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Python: Most Popular in 2018 and Dutch!
Guido van Rossum
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Ads Scripts vs Python vs R?
Ads Scripts Python R
Serverless
Direct Ads API
Many Packages
General Purpose
Machine Learning
( )
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No Either-Or: Run Python From Scripts
Scripts Cloud Functions
...
...
Demo: bit.ly/norisk_python
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Three Simpler Options To Tie in ML
Model 2. AutoML 1. Pretrained
ML API
WRITE TO
3. BigQuery ML
Your Script or Application
4. Custom Model
Source: Lak Lakshaman - Medium
Effort, Data, Accuracy
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Use Case #1: Classifying Near-Exact
Query Understanding
INTRO Machine Learning Essentials
1. Classifying Near-Exact
ML Toolkit For PPC Platforms & Tools
#FOS19
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Case #1: Classifying Near-Exact
Source: https://searchengineland.com/when-exact-match-isnt-exact-anymore-a-script-to-regain-control-307975
ONLY BLOCKING.
> What about EXPANSION?
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Classify Near Exact? Ask Google!
Demo: bit.ly/norisk_python
1. Suggest
2. Custom Search
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Auto ML I: Model scores & Prediction
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Auto ML II: Classifying Brand Campaigns
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Use Case #2: Ngram Analysis & BigQuery
Query Understanding
Prediction 2. Analysing Query n-Grams
INTRO Machine Learning Essentials
1. Classifying Near-Exact
ML Toolkit For PPC Platforms & Tools
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Remember This? BigQuery Is Faster!
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The Basis: Google Ads Data Transfer
Tutorial: https://www.excelinppc.com/big-query-automation-powerhouse-for-google-ads/
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Our Agenda: Intro & 3 PPC Use Cases
Query Understanding
Text Summarization
Prediction 2. Analysing Query n-Grams
3. Finding Key Phrases
INTRO Machine Learning Essentials
1. Classifying Near-Exact
ML Toolkit For PPC Platforms & Tools
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Takeaways: Start Experimenting!
USE CASES
INTRO Machine Learning Essentials
Typos, NGrams, Summaries
ML Toolkit For PPC Platforms & Tools
TAKEAWAYS Start Experimenting!
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AI Is Coming ? Let’s be Jon Snow!
1. Listen to Your Team’s problems
4. Be the Architect of Change
3. Leverage the Cloud’s Weapons
2. Learn the Craft of Tool Prototyping
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THANK YOU. Your Questions Please!
MACHINE LEARNING IN PPC
How To Get Started Today
Christopher Gutknecht | norisk Group | #FOS19
#FOS19
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Bonus: GA Anomaly Detection for Slack
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Our Agenda: Intro & 3 PPC Use Cases
USE CASES
APPENDIX I Additional Content
INTRO Machine Learning Essentials
Typos, NGrams, Summaries
ML Toolkit For PPC Platforms & Tools
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● Designed rule-flow● Outliers not included ● Won’t improve on data
Rule #1: Not Every Problem Needs ML
RULE BASED MACHINE LEARNING
● Algorithmic model● Model learns from errors ● Model constantly retrained
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Rule-Based vs Machine Learning Code
Source: Machine Learning 101 (Jason Myers, Google)
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Five Main Types of ML AlgorithmsSu
per
vise
d
Clustering Dimension Reduction
Classification Regression
+ Reinforcement Learning
Un
sup
ervi
sed
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Natural Language Processing Is Its Own Game
Sentiment Analysis Topic Modelling
Entity Recognition Sequence Prediction
Sup
ervi
sed
←
→ U
nsu
per
vise
d
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And Deep Learning? Higher Accuracy!
Source: https://blogs.sas.com/content/subconsciousmusings/2017/04/12/machine-learning-algorithm-use/#prettyPhoto/0/
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● Depth and Breadth● Cleanliness
Main Challenges for ML Approaches
● Choice of framework● References projects
Access To DataGood Problem Framing Knowledge of Solutions
● Finding value drivers● Defining relevant outputs
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The 3 Cloud Platforms & their ML Tools
+ Windows & Bing maybe
● “● “● “● -
Google Cloud Platform
+ Google Integrations
● Managed Storage ● Serverless Execution● Pretrained ML APIs● AutoML Service
Amazon Web Services Microsoft Azure
+ Best DevOps Workflow
● “● “● “● “
→ All similar. But Google has its benefits!
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Pretrained APIs: Amazon Comprehend
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
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Look out for Colab: Example TensorFlow
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Popular Python NLP Packages
fuzzyWuzzy
String Similarity Language Model Context Modeling
Fuzzy Wuzzy Cloud Function Example:
https://colab.research.google.com/drive/1W6guxVZJqp-duQT6jSlmsqxkrCgt95Cl#scrollTo=a60zDUMiOEXD
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Sixt: Query Disambiguation via App & Spacy
Improve Training Data
I think it is a VEHICLE_TYPE
bristol car & van hire
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Don’t want write code? Try KNIME
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Our Agenda: Intro & 3 PPC Use Cases
USE CASES
APPENDIX II Resources
INTRO Machine Learning Essentials
Typos, NGrams, Auto-Sitelinks
ML Toolkit For PPC Platforms & Tools
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Resources: Google ML Crash Course
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
developers.google.com/machine-learning/crash-course/
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Resources: ai.google/education
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
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Resources: cloud.google.training
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
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Resources: codelabs.google.com
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
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Resources: aws.training (Courses)
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
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Resources: aws.training
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=best
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Resources: Machine Learning 101
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=bestdocs.google.com/presentation/d/1kSuQyW5DTnkVaZEjGYCkfOxvzCqGEFzWBy4e9Uedd9k/
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Resources: TechSEO Boost (Python/ML)
https://www.istockphoto.com/de/fotos/tourist-in-china?page=2&phrase=tourist%20in%20china&sort=bestPython & SEO Talks @ TechSEOBoost: https://youtu.be/N0uJp_JXfOg
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Resources: Scraping with Python
Python Scrapy Tutorial: https://youtu.be/ve_0h4Y8nuI