SlideShare a Scribd company logo
Factorization
Machines
St. Petersburg Data Science Meetup, May, 29th, 2015
@facultyofwonder Rutarget/Segmento
credits: https://twitter.com/ejlbell/status/559772240544563201
Q: What, say, 3 recent papers in machine learning do you think will be influential to directing the cutting edge
of research these days?
Peter Norvig: I’ve never been able to pick lasting papers in the past, so don’t trust me now, but here are a few:
● Rendle’s “Factorization Machines”
● Wang et al. “Bayesian optimization in high dimensions via random embeddings”
● Dean et al. “Fast, Accurate Detection of 100,000 Object Classes on a Single Machine”
http://blog.teamleada.com/2014/08/ask-peter-norvig/
Criteo Dataset: http://labs.criteo.com/downloads/download-terabyte-click-logs/
Data
Lots of categorical features
Sparse settings
Pairwise interactions
Hashing trick?
Linear model
Polynomial features
independent interactions
Factorization
breaking the independence of
interaction parameters
Example
U = {Alice (A), Bob (B), Charlie (C), . . .}
I = {Titanic (TI), Notting Hill (NH), Star Wars
(SW), Star Trek (ST), . . .}
Example
{(A, TI, 2010-1, 5),(A, NH, 2010-2, 3),(A, SW,
2010-4, 1), (B, SW, 2009-5, 4),(B, ST, 2009-8,
5), (C, TI, 2009-9, 1),(C, SW, 2009-12, 5)}
Interaction between Alice and Star Trek to predict rating?
Zero interaction?
B-SW and C-SW are similar
A and C are different
ST and SW are similar
A-SW and A-ST are to be similar
Complexity
Number of parameters:
1 + p + k * p
Linear to the input size and the size of
factorization
Regularization
Many parameters, prone to overfitting
L2 regularization
LR+FM+SGD
Learning
Learning
bit.ly/pyfm_demo
Hyperparameters
Number of factors
Regularization
Learning rate
Initial weights
FFM:ideas
Features can be grouped into fields: users,
movies, context, SSPs, publishers, whatever
Better use this information
Factor vector per field
Summary
Factorized interactions
High sparsity is OK for parameters estimation
Papers,papers
bit.ly/factorization_machines_2010
bit.ly/libfm
bit.ly/field_aware_FM

More Related Content

What's hot

Feature selection
Feature selectionFeature selection
Feature selection
Dong Guo
 
An introduction to Recommender Systems
An introduction to Recommender SystemsAn introduction to Recommender Systems
An introduction to Recommender Systems
David Zibriczky
 
Graph database
Graph database Graph database
Graph database
Shruti Arya
 
Data Science Full Course | Edureka
Data Science Full Course | EdurekaData Science Full Course | Edureka
Data Science Full Course | Edureka
Edureka!
 
Graph databases
Graph databasesGraph databases
Graph databases
Karol Grzegorczyk
 
Feature Engineering
Feature EngineeringFeature Engineering
Feature Engineering
HJ van Veen
 
[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정
[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정
[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정
PAP (Product Analytics Playground)
 
Recommender Systems
Recommender SystemsRecommender Systems
Recommender Systems
Carlos Castillo (ChaTo)
 
Matrix Factorization Techniques For Recommender Systems
Matrix Factorization Techniques For Recommender SystemsMatrix Factorization Techniques For Recommender Systems
Matrix Factorization Techniques For Recommender Systems
Lei Guo
 
Cross-validation Tutorial: What, how and which?
Cross-validation Tutorial: What, how and which?Cross-validation Tutorial: What, how and which?
Cross-validation Tutorial: What, how and which?
Pradeep Redddy Raamana
 
Matrix Factorization
Matrix FactorizationMatrix Factorization
Matrix Factorization
Yusuke Yamamoto
 
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...
Edureka!
 
Big Data Proof of Concept
Big Data Proof of ConceptBig Data Proof of Concept
Big Data Proof of Concept
RCG Global Services
 
Feature Engineering in Machine Learning
Feature Engineering in Machine LearningFeature Engineering in Machine Learning
Feature Engineering in Machine Learning
Knoldus Inc.
 
Link prediction
Link predictionLink prediction
Link prediction
Carlos Castillo (ChaTo)
 
Feature Engineering - Getting most out of data for predictive models
Feature Engineering - Getting most out of data for predictive modelsFeature Engineering - Getting most out of data for predictive models
Feature Engineering - Getting most out of data for predictive models
Gabriel Moreira
 
NLP Bootcamp 2018 : Representation Learning of text for NLP
NLP Bootcamp 2018 : Representation Learning of text for NLPNLP Bootcamp 2018 : Representation Learning of text for NLP
NLP Bootcamp 2018 : Representation Learning of text for NLP
Anuj Gupta
 
K-means and GMM
K-means and GMMK-means and GMM
K-means and GMM
Sanghyuk Chun
 
Machine Learning Interpretability
Machine Learning InterpretabilityMachine Learning Interpretability
Machine Learning Interpretability
inovex GmbH
 
Diversity and novelty for recommendation system
Diversity and novelty for recommendation systemDiversity and novelty for recommendation system
Diversity and novelty for recommendation system
Zhenv5
 

What's hot (20)

Feature selection
Feature selectionFeature selection
Feature selection
 
An introduction to Recommender Systems
An introduction to Recommender SystemsAn introduction to Recommender Systems
An introduction to Recommender Systems
 
Graph database
Graph database Graph database
Graph database
 
Data Science Full Course | Edureka
Data Science Full Course | EdurekaData Science Full Course | Edureka
Data Science Full Course | Edureka
 
Graph databases
Graph databasesGraph databases
Graph databases
 
Feature Engineering
Feature EngineeringFeature Engineering
Feature Engineering
 
[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정
[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정
[팝콘 시즌1] 허현 : 닭이 먼저 달걀이 먼저? 그래인저 인과검정
 
Recommender Systems
Recommender SystemsRecommender Systems
Recommender Systems
 
Matrix Factorization Techniques For Recommender Systems
Matrix Factorization Techniques For Recommender SystemsMatrix Factorization Techniques For Recommender Systems
Matrix Factorization Techniques For Recommender Systems
 
Cross-validation Tutorial: What, how and which?
Cross-validation Tutorial: What, how and which?Cross-validation Tutorial: What, how and which?
Cross-validation Tutorial: What, how and which?
 
Matrix Factorization
Matrix FactorizationMatrix Factorization
Matrix Factorization
 
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning A...
 
Big Data Proof of Concept
Big Data Proof of ConceptBig Data Proof of Concept
Big Data Proof of Concept
 
Feature Engineering in Machine Learning
Feature Engineering in Machine LearningFeature Engineering in Machine Learning
Feature Engineering in Machine Learning
 
Link prediction
Link predictionLink prediction
Link prediction
 
Feature Engineering - Getting most out of data for predictive models
Feature Engineering - Getting most out of data for predictive modelsFeature Engineering - Getting most out of data for predictive models
Feature Engineering - Getting most out of data for predictive models
 
NLP Bootcamp 2018 : Representation Learning of text for NLP
NLP Bootcamp 2018 : Representation Learning of text for NLPNLP Bootcamp 2018 : Representation Learning of text for NLP
NLP Bootcamp 2018 : Representation Learning of text for NLP
 
K-means and GMM
K-means and GMMK-means and GMM
K-means and GMM
 
Machine Learning Interpretability
Machine Learning InterpretabilityMachine Learning Interpretability
Machine Learning Interpretability
 
Diversity and novelty for recommendation system
Diversity and novelty for recommendation systemDiversity and novelty for recommendation system
Diversity and novelty for recommendation system
 

Viewers also liked

آموزش محاسبات عددی - بخش دوم
آموزش محاسبات عددی - بخش دومآموزش محاسبات عددی - بخش دوم
آموزش محاسبات عددی - بخش دوم
faradars
 
Recommender system introduction
Recommender system   introductionRecommender system   introduction
Recommender system introduction
Liang Xiang
 
Neighbor methods vs matrix factorization - case studies of real-life recommen...
Neighbor methods vs matrix factorization - case studies of real-life recommen...Neighbor methods vs matrix factorization - case studies of real-life recommen...
Neighbor methods vs matrix factorization - case studies of real-life recommen...
Domonkos Tikk
 
Nonnegative Matrix Factorization
Nonnegative Matrix FactorizationNonnegative Matrix Factorization
Nonnegative Matrix Factorization
Tatsuya Yokota
 
Matrix factorization
Matrix factorizationMatrix factorization
Matrix factorization
rubyyc
 
Lecture 6 lu factorization & determinants - section 2-5 2-7 3-1 and 3-2
Lecture 6   lu factorization & determinants - section 2-5 2-7 3-1 and 3-2Lecture 6   lu factorization & determinants - section 2-5 2-7 3-1 and 3-2
Lecture 6 lu factorization & determinants - section 2-5 2-7 3-1 and 3-2
njit-ronbrown
 
Factorization Machines with libFM
Factorization Machines with libFMFactorization Machines with libFM
Factorization Machines with libFM
Liangjie Hong
 
Collaborative Filtering with Spark
Collaborative Filtering with SparkCollaborative Filtering with Spark
Collaborative Filtering with Spark
Chris Johnson
 
Matrix Factorization Technique for Recommender Systems
Matrix Factorization Technique for Recommender SystemsMatrix Factorization Technique for Recommender Systems
Matrix Factorization Technique for Recommender Systems
Aladejubelo Oluwashina
 
Recommender Systems
Recommender SystemsRecommender Systems
Recommender Systems
Girish Khanzode
 
Introduction to Matrix Factorization Methods Collaborative Filtering
Introduction to Matrix Factorization Methods Collaborative FilteringIntroduction to Matrix Factorization Methods Collaborative Filtering
Introduction to Matrix Factorization Methods Collaborative Filtering
DKALab
 
Beginners Guide to Non-Negative Matrix Factorization
Beginners Guide to Non-Negative Matrix FactorizationBeginners Guide to Non-Negative Matrix Factorization
Beginners Guide to Non-Negative Matrix Factorization
Benjamin Bengfort
 
Recommender Systems
Recommender SystemsRecommender Systems
Recommender Systems
T212
 
Recommendation system
Recommendation system Recommendation system
Recommendation system
Vikrant Arya
 
Collaborative Filtering Recommendation System
Collaborative Filtering Recommendation SystemCollaborative Filtering Recommendation System
Collaborative Filtering Recommendation System
Milind Gokhale
 
Building a Recommendation Engine - An example of a product recommendation engine
Building a Recommendation Engine - An example of a product recommendation engineBuilding a Recommendation Engine - An example of a product recommendation engine
Building a Recommendation Engine - An example of a product recommendation engine
NYC Predictive Analytics
 
Recommender system algorithm and architecture
Recommender system algorithm and architectureRecommender system algorithm and architecture
Recommender system algorithm and architecture
Liang Xiang
 

Viewers also liked (17)

آموزش محاسبات عددی - بخش دوم
آموزش محاسبات عددی - بخش دومآموزش محاسبات عددی - بخش دوم
آموزش محاسبات عددی - بخش دوم
 
Recommender system introduction
Recommender system   introductionRecommender system   introduction
Recommender system introduction
 
Neighbor methods vs matrix factorization - case studies of real-life recommen...
Neighbor methods vs matrix factorization - case studies of real-life recommen...Neighbor methods vs matrix factorization - case studies of real-life recommen...
Neighbor methods vs matrix factorization - case studies of real-life recommen...
 
Nonnegative Matrix Factorization
Nonnegative Matrix FactorizationNonnegative Matrix Factorization
Nonnegative Matrix Factorization
 
Matrix factorization
Matrix factorizationMatrix factorization
Matrix factorization
 
Lecture 6 lu factorization & determinants - section 2-5 2-7 3-1 and 3-2
Lecture 6   lu factorization & determinants - section 2-5 2-7 3-1 and 3-2Lecture 6   lu factorization & determinants - section 2-5 2-7 3-1 and 3-2
Lecture 6 lu factorization & determinants - section 2-5 2-7 3-1 and 3-2
 
Factorization Machines with libFM
Factorization Machines with libFMFactorization Machines with libFM
Factorization Machines with libFM
 
Collaborative Filtering with Spark
Collaborative Filtering with SparkCollaborative Filtering with Spark
Collaborative Filtering with Spark
 
Matrix Factorization Technique for Recommender Systems
Matrix Factorization Technique for Recommender SystemsMatrix Factorization Technique for Recommender Systems
Matrix Factorization Technique for Recommender Systems
 
Recommender Systems
Recommender SystemsRecommender Systems
Recommender Systems
 
Introduction to Matrix Factorization Methods Collaborative Filtering
Introduction to Matrix Factorization Methods Collaborative FilteringIntroduction to Matrix Factorization Methods Collaborative Filtering
Introduction to Matrix Factorization Methods Collaborative Filtering
 
Beginners Guide to Non-Negative Matrix Factorization
Beginners Guide to Non-Negative Matrix FactorizationBeginners Guide to Non-Negative Matrix Factorization
Beginners Guide to Non-Negative Matrix Factorization
 
Recommender Systems
Recommender SystemsRecommender Systems
Recommender Systems
 
Recommendation system
Recommendation system Recommendation system
Recommendation system
 
Collaborative Filtering Recommendation System
Collaborative Filtering Recommendation SystemCollaborative Filtering Recommendation System
Collaborative Filtering Recommendation System
 
Building a Recommendation Engine - An example of a product recommendation engine
Building a Recommendation Engine - An example of a product recommendation engineBuilding a Recommendation Engine - An example of a product recommendation engine
Building a Recommendation Engine - An example of a product recommendation engine
 
Recommender system algorithm and architecture
Recommender system algorithm and architectureRecommender system algorithm and architecture
Recommender system algorithm and architecture
 

Similar to Intro to Factorization Machines

Data Citation Made Easy
Data Citation Made EasyData Citation Made Easy
Gridforum David De Roure Newe Science 20080402
Gridforum David De Roure Newe Science 20080402Gridforum David De Roure Newe Science 20080402
Gridforum David De Roure Newe Science 20080402
vrij
 
Data Engine
Data EngineData Engine
Data Engine
DevCSI
 
Democratizing Data Science by Bill Howe
Democratizing Data Science by Bill HoweDemocratizing Data Science by Bill Howe
Democratizing Data Science by Bill Howe
InfinIT - Innovationsnetværket for it
 
Real World NLP, ML, and Big Data
Real World NLP, ML, and Big DataReal World NLP, ML, and Big Data
Real World NLP, ML, and Big Data
Devin Bost
 
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...
Spark Summit
 
Ia Summit08 Wa Slides
Ia Summit08 Wa SlidesIa Summit08 Wa Slides
Ia Summit08 Wa Slides
guest9f924a
 
The New e-Science (Bangalore Edition)
The New e-Science (Bangalore Edition)The New e-Science (Bangalore Edition)
The New e-Science (Bangalore Edition)
David De Roure
 
Take a Lesson From the Research World - Strata OLC
Take a Lesson From the Research World - Strata OLCTake a Lesson From the Research World - Strata OLC
Take a Lesson From the Research World - Strata OLC
Kaitlin Thaney
 
Perspectives on chemical composition and crystal structure representations fr...
Perspectives on chemical composition and crystal structure representations fr...Perspectives on chemical composition and crystal structure representations fr...
Perspectives on chemical composition and crystal structure representations fr...
Anubhav Jain
 
Data science presentation
Data science presentationData science presentation
Data science presentation
MSDEVMTL
 
Using dataset versioning in data science
Using dataset versioning in data scienceUsing dataset versioning in data science
Using dataset versioning in data science
Venkata Pingali
 
Making friends with big data resource links
Making friends with big data resource linksMaking friends with big data resource links
Making friends with big data resource links
Heather Stark
 
Automated Machine Learning Applied to Diverse Materials Design Problems
Automated Machine Learning Applied to Diverse Materials Design ProblemsAutomated Machine Learning Applied to Diverse Materials Design Problems
Automated Machine Learning Applied to Diverse Materials Design Problems
Anubhav Jain
 
GeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data ScienceGeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data Science
Mark West
 
Finding Emerging Topics Using Chaos and Community Detection in Social Media G...
Finding Emerging Topics Using Chaos and Community Detection in Social Media G...Finding Emerging Topics Using Chaos and Community Detection in Social Media G...
Finding Emerging Topics Using Chaos and Community Detection in Social Media G...
Paragon_Science_Inc
 
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)
Stian Soiland-Reyes
 
Model evaluation in the land of deep learning
Model evaluation in the land of deep learningModel evaluation in the land of deep learning
Model evaluation in the land of deep learning
Pramit Choudhary
 
IJET-V3I2P2
IJET-V3I2P2IJET-V3I2P2
H2O World - Benchmarking Open Source ML Platforms - Szilard Pafka
H2O World - Benchmarking Open Source ML Platforms - Szilard PafkaH2O World - Benchmarking Open Source ML Platforms - Szilard Pafka
H2O World - Benchmarking Open Source ML Platforms - Szilard Pafka
Sri Ambati
 

Similar to Intro to Factorization Machines (20)

Data Citation Made Easy
Data Citation Made EasyData Citation Made Easy
Data Citation Made Easy
 
Gridforum David De Roure Newe Science 20080402
Gridforum David De Roure Newe Science 20080402Gridforum David De Roure Newe Science 20080402
Gridforum David De Roure Newe Science 20080402
 
Data Engine
Data EngineData Engine
Data Engine
 
Democratizing Data Science by Bill Howe
Democratizing Data Science by Bill HoweDemocratizing Data Science by Bill Howe
Democratizing Data Science by Bill Howe
 
Real World NLP, ML, and Big Data
Real World NLP, ML, and Big DataReal World NLP, ML, and Big Data
Real World NLP, ML, and Big Data
 
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...
 
Ia Summit08 Wa Slides
Ia Summit08 Wa SlidesIa Summit08 Wa Slides
Ia Summit08 Wa Slides
 
The New e-Science (Bangalore Edition)
The New e-Science (Bangalore Edition)The New e-Science (Bangalore Edition)
The New e-Science (Bangalore Edition)
 
Take a Lesson From the Research World - Strata OLC
Take a Lesson From the Research World - Strata OLCTake a Lesson From the Research World - Strata OLC
Take a Lesson From the Research World - Strata OLC
 
Perspectives on chemical composition and crystal structure representations fr...
Perspectives on chemical composition and crystal structure representations fr...Perspectives on chemical composition and crystal structure representations fr...
Perspectives on chemical composition and crystal structure representations fr...
 
Data science presentation
Data science presentationData science presentation
Data science presentation
 
Using dataset versioning in data science
Using dataset versioning in data scienceUsing dataset versioning in data science
Using dataset versioning in data science
 
Making friends with big data resource links
Making friends with big data resource linksMaking friends with big data resource links
Making friends with big data resource links
 
Automated Machine Learning Applied to Diverse Materials Design Problems
Automated Machine Learning Applied to Diverse Materials Design ProblemsAutomated Machine Learning Applied to Diverse Materials Design Problems
Automated Machine Learning Applied to Diverse Materials Design Problems
 
GeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data ScienceGeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data Science
 
Finding Emerging Topics Using Chaos and Community Detection in Social Media G...
Finding Emerging Topics Using Chaos and Community Detection in Social Media G...Finding Emerging Topics Using Chaos and Community Detection in Social Media G...
Finding Emerging Topics Using Chaos and Community Detection in Social Media G...
 
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)
 
Model evaluation in the land of deep learning
Model evaluation in the land of deep learningModel evaluation in the land of deep learning
Model evaluation in the land of deep learning
 
IJET-V3I2P2
IJET-V3I2P2IJET-V3I2P2
IJET-V3I2P2
 
H2O World - Benchmarking Open Source ML Platforms - Szilard Pafka
H2O World - Benchmarking Open Source ML Platforms - Szilard PafkaH2O World - Benchmarking Open Source ML Platforms - Szilard Pafka
H2O World - Benchmarking Open Source ML Platforms - Szilard Pafka
 

Recently uploaded

一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
nuttdpt
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
nuttdpt
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Kiwi Creative
 
一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理
一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理
一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理
y3i0qsdzb
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
roli9797
 
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
nyfuhyz
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Fernanda Palhano
 
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Walaa Eldin Moustafa
 
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docxDATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
SaffaIbrahim1
 
Challenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more importantChallenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more important
Sm321
 
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Kaxil Naik
 
一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理
一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理
一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理
xclpvhuk
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
aqzctr7x
 
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Aggregage
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
AndrzejJarynowski
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
apvysm8
 
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
Social Samosa
 
Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......
Sachin Paul
 
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
a9qfiubqu
 
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
mkkikqvo
 

Recently uploaded (20)

一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
 
一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理
一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理
一比一原版巴斯大学毕业证(Bath毕业证书)学历如何办理
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
 
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
 
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
 
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docxDATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
 
Challenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more importantChallenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more important
 
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
 
一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理
一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理
一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
 
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
 
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
 
Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......
 
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
 
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
 

Intro to Factorization Machines