SlideShare a Scribd company logo
1 of 40
Download to read offline
SciPy 2010 Review
Eric Jones • July 16, 2010
187 attendees.
187 attendees
           120 Tutorials
            50 Sprints
187 attendees
             120 Tutorials
               50 Sprints
                    •
        96 Industry/Government
             57 Academics
              36 Students
187 attendees
          >50% growth rate
             from 2009
                   •
         EuroSciPy 2010 had
           140 attendees...
         >100-200% growth!
Major Theme:
Parallel Computing and GPUs
Parallel Computing and GPUs
TUTORIAL: High Performance & Parallel Computing
          Brian Granger




                              Multiple libraries for a similar task:
                              • Multiprocessing
                              • MPI4Py
                              • PyZMQ
                              • IPython
                              • PiCloud
Parallel Computing and GPUs
TUTORIAL: GPUs and Python
          Andreas Klockner
Parallel Computing and GPUs
KEYNOTE:   Python Concurrency
           David Beazley
Parallel Computing and GPUs
GENERAL SESSION:              Theano: Transparent GPU computing
James Bergstra, Olivier Breuleux, Frederic Bastien, Pascal Lamblin, Razvan
Pascanu, Guillaume Desjardins, Joseph Turian, Yoshua Bengio
Parallel Computing and GPUs
GENERAL SESSION: Simple, Fast Messaging in Python
          with 0MQ and PyZMQ         Brian Granger
Parallel Computing and GPUs




SPECIALIZED TRACK....

   Dan Yamins, StarFlow ➞
Minor Theme:
Stats (and the data structures for them)
Stats (and the data structures for them)
GENERAL SESSION:

Statsmodels             Pandas
Skipper Seabold         Wes McKinney
Stats (and the data structures for them)
 BOFs
                         Wiki


http://projects.scipy.org/numpy/wiki/NdarrayWithNamedAxes
                                                                      Docs


                                                            http://fperez.org/py4science/datarray/
Stats (and the data structures for them)
Sprints   Warren Weckesser, Anthony Scopatz

                           •   Added tests to scipy.stats to
                               bring it more in line with testing
                               in other SciPy packages.
                           •   Added a preliminary N-
                               dimensional contingency table
                               model with tests.
                           •   Skipper Seabold worked on a
                               refactor of scipy.stats
                               distributions. 
Minor Theme:
BioInformatics
Bioinformatics
Other Interesting Talks...
KEYNOTE: Moving Forward from the Last Decade of SciPy
Travis Oliphant
Divisi: Learning from Semantic Networks and Sparse SVD
Rob Speer
Do Google, Bing, & Yahoo Differ?
Contingency Table Analysis on Search Engines
Anthony Scopatz
Python Evangelism 101 (Lightning talk)
Peter Wang
Various Astronomy talks...
Rebuilding the Hubble                       Keeping the Chandra Satellite
Exposure Time Calculator                    Cool with Python
Perry Greenfield                            Tom Aldcroft




SpacePy: A Python-based library of tools    Astrodata
for the space sciences                      Craig Allen
Steven K. Morley, Josef Koller, Daniel T.
Welling, Michael G. Henderson
Sprints
PyZMQ
NumPy
datetime
Thank you.

More Related Content

What's hot

私は如何にして心配するのを止めてPyTorchを愛するようになったか
私は如何にして心配するのを止めてPyTorchを愛するようになったか私は如何にして心配するのを止めてPyTorchを愛するようになったか
私は如何にして心配するのを止めてPyTorchを愛するようになったか
Yuta Kashino
 
Python for Financial Data Analysis with pandas
Python for Financial Data Analysis with pandasPython for Financial Data Analysis with pandas
Python for Financial Data Analysis with pandas
Wes McKinney
 

What's hot (19)

Real-Time Big Data Stream Analytics
Real-Time Big Data Stream AnalyticsReal-Time Big Data Stream Analytics
Real-Time Big Data Stream Analytics
 
PyTorch 튜토리얼 (Touch to PyTorch)
PyTorch 튜토리얼 (Touch to PyTorch)PyTorch 튜토리얼 (Touch to PyTorch)
PyTorch 튜토리얼 (Touch to PyTorch)
 
Intermediate python ch1_slides
Intermediate python ch1_slidesIntermediate python ch1_slides
Intermediate python ch1_slides
 
MOA for the IoT at ACML 2016
MOA for the IoT at ACML 2016 MOA for the IoT at ACML 2016
MOA for the IoT at ACML 2016
 
深層学習フレームワーク概要とChainerの事例紹介
深層学習フレームワーク概要とChainerの事例紹介深層学習フレームワーク概要とChainerの事例紹介
深層学習フレームワーク概要とChainerの事例紹介
 
A Short Course in Data Stream Mining
A Short Course in Data Stream MiningA Short Course in Data Stream Mining
A Short Course in Data Stream Mining
 
私は如何にして心配するのを止めてPyTorchを愛するようになったか
私は如何にして心配するのを止めてPyTorchを愛するようになったか私は如何にして心配するのを止めてPyTorchを愛するようになったか
私は如何にして心配するのを止めてPyTorchを愛するようになったか
 
Numba
NumbaNumba
Numba
 
SciPy Latin America 2019
SciPy Latin America 2019SciPy Latin America 2019
SciPy Latin America 2019
 
TensorFrames: Google Tensorflow on Apache Spark
TensorFrames: Google Tensorflow on Apache SparkTensorFrames: Google Tensorflow on Apache Spark
TensorFrames: Google Tensorflow on Apache Spark
 
Beyond EXPLAIN: Query Optimization From Theory To Code
Beyond EXPLAIN: Query Optimization From Theory To CodeBeyond EXPLAIN: Query Optimization From Theory To Code
Beyond EXPLAIN: Query Optimization From Theory To Code
 
Machine Intelligence at Google Scale: TensorFlow
Machine Intelligence at Google Scale: TensorFlowMachine Intelligence at Google Scale: TensorFlow
Machine Intelligence at Google Scale: TensorFlow
 
Real Time Big Data Management
Real Time Big Data ManagementReal Time Big Data Management
Real Time Big Data Management
 
TENSORFLOW: ARCHITECTURE AND USE CASE - NASA SPACE APPS CHALLENGE by Gema Par...
TENSORFLOW: ARCHITECTURE AND USE CASE - NASA SPACE APPS CHALLENGE by Gema Par...TENSORFLOW: ARCHITECTURE AND USE CASE - NASA SPACE APPS CHALLENGE by Gema Par...
TENSORFLOW: ARCHITECTURE AND USE CASE - NASA SPACE APPS CHALLENGE by Gema Par...
 
Matplotlib Review 2021
Matplotlib Review 2021Matplotlib Review 2021
Matplotlib Review 2021
 
TensorFlow Dev Summit 2017 요약
TensorFlow Dev Summit 2017 요약TensorFlow Dev Summit 2017 요약
TensorFlow Dev Summit 2017 요약
 
Koss 1605 machine_learning_mariocho_t10
Koss 1605 machine_learning_mariocho_t10Koss 1605 machine_learning_mariocho_t10
Koss 1605 machine_learning_mariocho_t10
 
Python for Financial Data Analysis with pandas
Python for Financial Data Analysis with pandasPython for Financial Data Analysis with pandas
Python for Financial Data Analysis with pandas
 
Icpp power ai-workshop 2018
Icpp power ai-workshop 2018Icpp power ai-workshop 2018
Icpp power ai-workshop 2018
 

Viewers also liked

Natural Language Processing in Practice
Natural Language Processing in PracticeNatural Language Processing in Practice
Natural Language Processing in Practice
Vsevolod Dyomkin
 
Nltk:a tool for_nlp - py_con-dhaka-2014
Nltk:a tool for_nlp - py_con-dhaka-2014Nltk:a tool for_nlp - py_con-dhaka-2014
Nltk:a tool for_nlp - py_con-dhaka-2014
Fasihul Kabir
 
DIY Deep Learning with Caffe Workshop
DIY Deep Learning with Caffe WorkshopDIY Deep Learning with Caffe Workshop
DIY Deep Learning with Caffe Workshop
odsc
 
Practical Natural Language Processing
Practical Natural Language ProcessingPractical Natural Language Processing
Practical Natural Language Processing
Jaganadh Gopinadhan
 

Viewers also liked (20)

Data science-toolchain
Data science-toolchainData science-toolchain
Data science-toolchain
 
Theano tutorial
Theano tutorialTheano tutorial
Theano tutorial
 
H2ODeepLearningThroughExamples021215
H2ODeepLearningThroughExamples021215H2ODeepLearningThroughExamples021215
H2ODeepLearningThroughExamples021215
 
Deep learning tutorial with theano study - CH 3, CH 4
Deep learning tutorial with theano study - CH 3, CH 4Deep learning tutorial with theano study - CH 3, CH 4
Deep learning tutorial with theano study - CH 3, CH 4
 
The top-10-secrets-of-nlp-coaching-language
The top-10-secrets-of-nlp-coaching-languageThe top-10-secrets-of-nlp-coaching-language
The top-10-secrets-of-nlp-coaching-language
 
Natural Language Processing in Practice
Natural Language Processing in PracticeNatural Language Processing in Practice
Natural Language Processing in Practice
 
Neural networks and google tensor flow
Neural networks and google tensor flowNeural networks and google tensor flow
Neural networks and google tensor flow
 
PageRank and Markov Chain
PageRank and Markov ChainPageRank and Markov Chain
PageRank and Markov Chain
 
(Kpi summer school 2015) theano tutorial part1
(Kpi summer school 2015) theano tutorial part1(Kpi summer school 2015) theano tutorial part1
(Kpi summer school 2015) theano tutorial part1
 
DF1 - Py - Ovcharenko - Theano Tutorial
DF1 - Py - Ovcharenko - Theano TutorialDF1 - Py - Ovcharenko - Theano Tutorial
DF1 - Py - Ovcharenko - Theano Tutorial
 
(Kpi summer school 2015) theano tutorial part2
(Kpi summer school 2015) theano tutorial part2(Kpi summer school 2015) theano tutorial part2
(Kpi summer school 2015) theano tutorial part2
 
Nltk:a tool for_nlp - py_con-dhaka-2014
Nltk:a tool for_nlp - py_con-dhaka-2014Nltk:a tool for_nlp - py_con-dhaka-2014
Nltk:a tool for_nlp - py_con-dhaka-2014
 
Natural Language Toolkit (NLTK), Basics
Natural Language Toolkit (NLTK), Basics Natural Language Toolkit (NLTK), Basics
Natural Language Toolkit (NLTK), Basics
 
NLTK: Natural Language Processing made easy
NLTK: Natural Language Processing made easyNLTK: Natural Language Processing made easy
NLTK: Natural Language Processing made easy
 
Urs Köster - Convolutional and Recurrent Neural Networks
Urs Köster - Convolutional and Recurrent Neural NetworksUrs Köster - Convolutional and Recurrent Neural Networks
Urs Köster - Convolutional and Recurrent Neural Networks
 
DIY Deep Learning with Caffe Workshop
DIY Deep Learning with Caffe WorkshopDIY Deep Learning with Caffe Workshop
DIY Deep Learning with Caffe Workshop
 
NLTK in 20 minutes
NLTK in 20 minutesNLTK in 20 minutes
NLTK in 20 minutes
 
Differences of Deep Learning Frameworks
Differences of Deep Learning FrameworksDifferences of Deep Learning Frameworks
Differences of Deep Learning Frameworks
 
Machine learning for dummies
Machine learning for dummiesMachine learning for dummies
Machine learning for dummies
 
Practical Natural Language Processing
Practical Natural Language ProcessingPractical Natural Language Processing
Practical Natural Language Processing
 

Similar to SciPy 2010 Review

The Joy of SciPy, Part I
The Joy of SciPy, Part IThe Joy of SciPy, Part I
The Joy of SciPy, Part I
Dinu Gherman
 
2014 manchester-reproducibility
2014 manchester-reproducibility2014 manchester-reproducibility
2014 manchester-reproducibility
c.titus.brown
 
1203 ipython pycon
1203 ipython pycon1203 ipython pycon
1203 ipython pycon
kkumar9034
 

Similar to SciPy 2010 Review (20)

Array computing and the evolution of SciPy, NumPy, and PyData
Array computing and the evolution of SciPy, NumPy, and PyDataArray computing and the evolution of SciPy, NumPy, and PyData
Array computing and the evolution of SciPy, NumPy, and PyData
 
Scientific Computing with Python Webinar --- August 28, 2009
Scientific Computing with Python Webinar --- August 28, 2009Scientific Computing with Python Webinar --- August 28, 2009
Scientific Computing with Python Webinar --- August 28, 2009
 
Intro to Python Data Analysis in Wakari
Intro to Python Data Analysis in WakariIntro to Python Data Analysis in Wakari
Intro to Python Data Analysis in Wakari
 
The Joy of SciPy, Part I
The Joy of SciPy, Part IThe Joy of SciPy, Part I
The Joy of SciPy, Part I
 
London level39
London level39London level39
London level39
 
3 python packages
3 python packages3 python packages
3 python packages
 
New Capabilities in the PyData Ecosystem
New Capabilities in the PyData EcosystemNew Capabilities in the PyData Ecosystem
New Capabilities in the PyData Ecosystem
 
Travis Oliphant "Python for Speed, Scale, and Science"
Travis Oliphant "Python for Speed, Scale, and Science"Travis Oliphant "Python for Speed, Scale, and Science"
Travis Oliphant "Python for Speed, Scale, and Science"
 
2014 nicta-reproducibility
2014 nicta-reproducibility2014 nicta-reproducibility
2014 nicta-reproducibility
 
Data_Science_Generating_Value_From_Data_Course_Slides_red.pdf
Data_Science_Generating_Value_From_Data_Course_Slides_red.pdfData_Science_Generating_Value_From_Data_Course_Slides_red.pdf
Data_Science_Generating_Value_From_Data_Course_Slides_red.pdf
 
Intro slides
Intro slidesIntro slides
Intro slides
 
PyTorch - an ecosystem for deep learning with Soumith Chintala (Facebook AI)
PyTorch - an ecosystem for deep learning with Soumith Chintala (Facebook AI)PyTorch - an ecosystem for deep learning with Soumith Chintala (Facebook AI)
PyTorch - an ecosystem for deep learning with Soumith Chintala (Facebook AI)
 
2019 03-11 bio it-world west genepattern notebook slides
2019 03-11 bio it-world west genepattern notebook slides2019 03-11 bio it-world west genepattern notebook slides
2019 03-11 bio it-world west genepattern notebook slides
 
Demystifying Machine Learning and Artificial Intelligence
Demystifying Machine Learning and Artificial IntelligenceDemystifying Machine Learning and Artificial Intelligence
Demystifying Machine Learning and Artificial Intelligence
 
2014 manchester-reproducibility
2014 manchester-reproducibility2014 manchester-reproducibility
2014 manchester-reproducibility
 
1203 ipython pycon
1203 ipython pycon1203 ipython pycon
1203 ipython pycon
 
2. Data Preprocessing.pdf
2. Data Preprocessing.pdf2. Data Preprocessing.pdf
2. Data Preprocessing.pdf
 
2014 pycon-talk
2014 pycon-talk2014 pycon-talk
2014 pycon-talk
 
Introduction to Recurrent Neural Network
Introduction to Recurrent Neural NetworkIntroduction to Recurrent Neural Network
Introduction to Recurrent Neural Network
 
How to interactively visualise and explore a billion objects (wit vaex)
How to interactively visualise and explore a billion objects (wit vaex)How to interactively visualise and explore a billion objects (wit vaex)
How to interactively visualise and explore a billion objects (wit vaex)
 

More from Enthought, Inc.

More from Enthought, Inc. (13)

Numpy Talk at SIAM
Numpy Talk at SIAMNumpy Talk at SIAM
Numpy Talk at SIAM
 
Talk at NYC Python Meetup Group
Talk at NYC Python Meetup GroupTalk at NYC Python Meetup Group
Talk at NYC Python Meetup Group
 
Scientific Applications with Python
Scientific Applications with PythonScientific Applications with Python
Scientific Applications with Python
 
Scientific Computing with Python Webinar March 19: 3D Visualization with Mayavi
Scientific Computing with Python Webinar March 19: 3D Visualization with MayaviScientific Computing with Python Webinar March 19: 3D Visualization with Mayavi
Scientific Computing with Python Webinar March 19: 3D Visualization with Mayavi
 
Chaco Step-by-Step
Chaco Step-by-StepChaco Step-by-Step
Chaco Step-by-Step
 
NumPy/SciPy Statistics
NumPy/SciPy StatisticsNumPy/SciPy Statistics
NumPy/SciPy Statistics
 
February EPD Webinar: How do I...use PiCloud for cloud computing?
February EPD Webinar: How do I...use PiCloud for cloud computing?February EPD Webinar: How do I...use PiCloud for cloud computing?
February EPD Webinar: How do I...use PiCloud for cloud computing?
 
SciPy India 2009
SciPy India 2009SciPy India 2009
SciPy India 2009
 
Parallel Processing with IPython
Parallel Processing with IPythonParallel Processing with IPython
Parallel Processing with IPython
 
Scientific Computing with Python Webinar: Traits
Scientific Computing with Python Webinar: TraitsScientific Computing with Python Webinar: Traits
Scientific Computing with Python Webinar: Traits
 
Scientific Computing with Python Webinar 9/18/2009:Curve Fitting
Scientific Computing with Python Webinar 9/18/2009:Curve FittingScientific Computing with Python Webinar 9/18/2009:Curve Fitting
Scientific Computing with Python Webinar 9/18/2009:Curve Fitting
 
Scientific Computing with Python Webinar --- June 19, 2009
Scientific Computing with Python Webinar --- June 19, 2009Scientific Computing with Python Webinar --- June 19, 2009
Scientific Computing with Python Webinar --- June 19, 2009
 
Scientific Computing with Python Webinar --- May 22, 2009
Scientific Computing with Python Webinar --- May 22, 2009Scientific Computing with Python Webinar --- May 22, 2009
Scientific Computing with Python Webinar --- May 22, 2009
 

Recently uploaded

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Recently uploaded (20)

Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Manulife - Insurer Innovation Award 2024
Manulife - Insurer Innovation Award 2024Manulife - Insurer Innovation Award 2024
Manulife - Insurer Innovation Award 2024
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Top 10 Most Downloaded Games on Play Store in 2024
Top 10 Most Downloaded Games on Play Store in 2024Top 10 Most Downloaded Games on Play Store in 2024
Top 10 Most Downloaded Games on Play Store in 2024
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 

SciPy 2010 Review