Blohm Lab Wiki - User contributions [en-ca]

Other Resources

2019-02-01T17:10:42Z

Brandon:

== Funding Opportunities ==
*[http://queensu.ca/sgs/sites/webpublish.queensu.ca.sgswww/files/files/Students/Queen's%20Presentation%20Graduate%20Students%20Morning%20April%2010th.pdf Mitacs graduate and post-doc funding (for private sector /NGO internships, or academic travel scholarships)]

== How to do science ==
* [http://compneurosci.com/wiki/index.php/Paper_Writing_101 Konrad's paper writing 101]
* Konrad's [http://biorxiv.org/content/early/2016/12/14/088278?utm_content=buffer8d04a&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer 10 simple rules for structuring papers] advice: read this before you start writing!!!
* [http://collections.plos.org/ten-simple-rules PLoS CB - 10 simple rules collection]: a must read for everyone!
* [http://colorbrewer2.org Colorbrewer]: great tool for selecting colour schemes on publications
* [http://neuronline.sfn.org/Articles/Professional-Development/2016/Tricks-of-the-Trade-How-to-Peer-Review-a-Manuscript How to peer review a manuscript]: Webinar and resources from SfN Neuronline.
* [http://neuronline.sfn.org/Articles/Career-Advice/2017/Tricks-of-the-Trade-Modelling-Papers-Resources How To Review Modelling Papers]: A webinar + resources from SfN Neuronline. The webinar date has passed, but if you 'register' there is an email link that will lead you to the archived video.
* [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4284499/ The pleasure of publishing (Malhotra & Marder, 2015)]: Elife editors' opinions on what makes an effective manuscript.
* [[Media:OpenScience.pdf | How to do Open Science slides]]
----

== How to be successful ==
* [https://www.technologyreview.com/s/409043/how-to-think/?utm_content=buffer9ea8e&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer Ed Boyden's advice on how to think]
* [http://www.wikihow.com/Think Developing better thought processes]
* [http://faculty.georgetown.edu/kingch/How_to_Think.htm How to argue well]
* [http://www.lifehack.org/articles/productivity/12-weekend-habits-highly-successful-people.html Habits for success]
* [http://www.cell.com/neuron/pdf/S0896-6273(15)00331-1.pdf Hitchhikers guide to a Career in Neuroscience]
* [http://www.programmerfu.com/2017/04/20/fast-is-slow-slow-is-smooth-smooth-is-fast.html Slow is smooth and smooth is fast]
* [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.462.8391&rep=rep1&type=pdf Survival Skills for Graduate School and Beyond] (Fischer and Zigmond, 1998; still very applicable)
* [https://www.cs.utexas.edu/users/EWD/transcriptions/EWD06xx/EWD637.html 3 golden rules of scientific success] by Dijkstra
----

== Work-life balance & mental health ==
As an undergraduate, graduate student or postdoc, as exciting a time as this is, you will face stress, frustration and deception. Your passion for science can suck up all your time and wack your physical and mental health out of balance. This can lead to a downward spiral out of which comes no good. Yes, grad school / postdoc work is hard, don't let it destroy you. So here are a few tips to avoid that in the first place.
* Get enough exercise and sleep!
* [http://www.nextscientist.com/work-life-balance-in-academia/ The Happy PhD zone]: how to maintain a work-life balance in academia
* [http://thegradstudentway.com/blog/?p=76#.WRZWlGfSkvc 6 Ways To Survive Grad School and Achieve Work-Life Balance]
* [https://www.mcgill.ca/gradsupervision/supervisees/work-life Official McGill University guidelines] on work-life balance
* [https://www.bustle.com/articles/87409-graduate-school-is-hard-so-here-are-8-simple-ways-to-maintain-your-sanity How to maintain your sanity] during grad school
* [https://psychcentral.com/lib/12-tips-for-surviving-and-thriving-in-grad-school/ Grad school survival tips]
* [http://www.sciencemag.org/careers/2018/08/three-reminders-help-you-thrive-not-merely-survive-grad-school Three reminders to help you thrive—not merely survive—in grad school]
* [http://www.nature.com/nature/journal/v545/n7654/full/nj7654-375a.html?WT.mc_id=FBK_NatureNews&sf79769979=1 Break or burn out]: a nice article in Nature
*[https://www.psychologytoday.com/files/attachments/1035/arts-foster-scientific-success.pdf Creative outlets and Scientific Success] Scientists are not more likely to have creative outlets, but the most successful ones are

== Resources for organizing a scientific project ==
*[https://towardsdatascience.com/how-to-keep-your-research-projects-organized-part-1-folder-structure-10bd56034d3a] How to keep your research projects organized, part 1: folder structure
*[http://nikola.me/folder_structure.html] Setting up an Organised Folder Structure for Research Projects
*[https://www.data.cam.ac.uk/data-management-guide/organising-your-data] Organising your data
*[http://help.osf.io/m/bestpractices/l/611391-organizing-files] OSF Guidelines
*[https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000424] A Quick Guide to Organizing Computational Biology Projects
*[https://evernote.com/] Evernote: Note taking app
*[https://trello.com/] Trello: Collaborate and share notes

IRTG

2018-04-24T15:01:59Z

Brandon: /* Professional Development Workshops */

== Professional Development Workshops ==
* [Apr 6, 2018] [[Media:Reliable_Open_Science_Practices.pdf ]] Brandon and Jonny's Open Science PD Talk

* [Apr 6, 2018] [[Media:IRTG_PD.pptx]] Brandon and Jonny's introduction on PD workshops

* [[Media:2017_Networking_Event_Program_Flyer.pdf]] Examples of Professional Development Workshops from SfN 2017.

*[Apr 24, 2018] [https://authorservices.wiley.com/asset/photos/promote.html/Full%20list%20of%20enrolled%20titles.xlsx List of Journals accepting video abstracts]

File:Reliable Open Science Practices.pdf

2018-04-24T15:01:47Z

Brandon:

IRTG

2018-04-24T15:00:25Z

Brandon: /* Professional Development Workshops */

== Professional Development Workshops ==
* [Apr 6, 2018] [[Media:Reliable_Open_Science_Practices.pptx]] Brandon and Jonny's Open Science PD Talk

* [Apr 6, 2018] [[Media:IRTG_PD.pptx]] Brandon and Jonny's introduction on PD workshops

* [[Media:2017_Networking_Event_Program_Flyer.pdf]] Examples of Professional Development Workshops from SfN 2017.

*[Apr 24, 2018] [https://authorservices.wiley.com/asset/photos/promote.html/Full%20list%20of%20enrolled%20titles.xlsx List of Journals accepting video abstracts]

File:IRTG PD.pptx

2018-04-06T17:06:47Z

Brandon:

Useful stuff

2017-09-26T13:46:53Z

Brandon: /* Work-life balance & mental health */

A list of useful resources on the web.

== General Math ==

* [https://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf Matrix cookbook]
* [http://www.cs.toronto.edu/~urtasun/courses/CV/lecture02.pdf Image filtering, edge detection, etc. (Computer vision)]
* [http://homepages.inf.ed.ac.uk/rbf/HIPR2/hough.htm Hough transform tutorial (Computer vision)]
* [http://www.cse.unr.edu/~bebis/CS474/Handouts/WaveletTutorial.pdf Introductory tutorial on Wavelet transforms]
*[http://download.springer.com/static/pdf/772/bok%253A978-1-4614-4984-3.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Fbook%2F10.1007%2F978-1-4614-4984-3&token2=exp=1474042019~acl=%2Fstatic%2Fpdf%2F772%2Fbok%25253A978-1-4614-4984-3.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Fbook%252F10.1007%252F978-1-4614-4984-3*~hmac=0a460b39cb2453dbeb442d3ac78432ef059788bc44ff8e4fe1c62fb8f57ec95f Imaging Brain Function with EEG: Advanced Temporal and Spatial Analysis of EEG Signals (Book by Walter J. Freeman)]
* [https://webfiles.uci.edu/mdlee/LeeWagenmakers2013_Free.pdf Bayesian Cognitive Modeling: A Practical Course]
----

== Statistics ==
* [http://onlinestatbook.com/2/index.html Rice University online Stats book]
* [http://www.leg.ufpr.br/~eder/Markov/Markov%20Chain%20Monte%20Carlo%20In%20Practice%20.pdf Markov Chain Monte Carlo in practice] - book
* [http://statweb.stanford.edu/~tibs/stat315a/Supplements/bootstrap.pdf Bootstrap methods & significance estimation]
* how to do [[Media:Repeated_ANOVA_MATLAB.pdf | repeated measures ANOVA]] in Matlab (by Parisa)
* [http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1004961 Ten Simple Rules for Effective Statistical Practice]
* [http://bootstrap-software.com/psignifit/publications/hill2001.pdf Testing Hypotheses About Psychometric Functions]
* [[Media:Latin_square_Method.pdf | Latin square method for experimental design]]
----

== General Comp Nsci ==
* [https://www.youtube.com/user/elscvideo/videos ELSC Youtube Channel] Contains archived computational neuroscience seminars and lectures, including Dayan, Abbot, Pouget..., as well as physiology resources.
* [https://www.coursera.org/learn/computational-neuroscience Coursera Computational Neuroscience] With instructors Rajesh Rao and Adrienne Fairhall.
* [http://www.shadmehrlab.org/lectures.html Reza Shadmehr lectures on motor control & learning]

----

== How to do science ==
* [http://klab.smpp.northwestern.edu/wiki/index.php5/Paper_Writing_101 Konrad's paper writing 101]
* Konrad's [http://biorxiv.org/content/early/2016/12/14/088278?utm_content=buffer8d04a&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer 10 simple rules for structuring papers] advice: read this before you start writing!!!
* [http://collections.plos.org/ten-simple-rules PLoS CB - 10 simple rules collection]: a must read for everyone!
* [http://colorbrewer2.org Colorbrewer]: great tool for selecting colour schemes on publications
* [http://neuronline.sfn.org/Articles/Professional-Development/2016/Tricks-of-the-Trade-How-to-Peer-Review-a-Manuscript How to peer review a manuscript]: Webinar and resources from SfN Neuronline.
* [http://neuronline.sfn.org/Articles/Career-Advice/2017/Tricks-of-the-Trade-Modelling-Papers-Resources How To Review Modelling Papers]: A webinar + resources from SfN Neuronline. The webinar date has passed, but if you 'register' there is an email link that will lead you to the archived video.
* [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4284499/ The pleasure of publishing (Malhotra & Marder, 2015)]: Elife editors' opinions on what makes an effective manuscript.
----

== How to be successful ==
* [https://www.technologyreview.com/s/409043/how-to-think/?utm_content=buffer9ea8e&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer Ed Boyden's advice on how to think]
* [http://www.wikihow.com/Think Developing better thought processes]
* [http://faculty.georgetown.edu/kingch/How_to_Think.htm How to argue well]
* [http://www.lifehack.org/articles/productivity/12-weekend-habits-highly-successful-people.html Habits for success]
* [http://www.cell.com/neuron/pdf/S0896-6273(15)00331-1.pdf Hitchhikers guide to a Career in Neuroscience]
* [http://www.programmerfu.com/2017/04/20/fast-is-slow-slow-is-smooth-smooth-is-fast.html Slow is smooth and smooth is fast]
----

== Work-life balance & mental health ==

As an undergraduate, graduate student or postdoc, as exciting a time as this is, you will face stress, frustration and deception. Your passion for science can suck up all your time and wack your physical and mental health out of balance. This can lead to a downward spiral out of which comes no good. Yes, grad school / postdoc work is hard, don't let it destroy you. So here are a few tips to avoid that in the first place.
* Get enough exercise and sleep!
* [http://www.nextscientist.com/work-life-balance-in-academia/ The Happy PhD zone]: how to maintain a work-life balance in academia
* [http://thegradstudentway.com/blog/?p=76#.WRZWlGfSkvc 6 Ways To Survive Grad School and Achieve Work-Life Balance]
* [https://www.mcgill.ca/gradsupervision/supervisees/work-life Official McGill University guidelines] on work-life balance
* [https://www.bustle.com/articles/87409-graduate-school-is-hard-so-here-are-8-simple-ways-to-maintain-your-sanity How to maintain your sanity] during grad school
* [https://psychcentral.com/lib/12-tips-for-surviving-and-thriving-in-grad-school/ Grad school survival tips]
* [http://www.nature.com/nature/journal/v545/n7654/full/nj7654-375a.html?WT.mc_id=FBK_NatureNews&sf79769979=1 Break or burn out]: a nice article in Nature
*[https://www.psychologytoday.com/files/attachments/1035/arts-foster-scientific-success.pdf Creative outlets and Scientific Success] Scientists are not more likely to have creative outlets, but the most successful ones are

Journal Club

2017-09-26T13:39:17Z

Brandon:

Archive of Journal Club Presentations:
* [Aug 30, 2017] Shmuelof and Krakauer, 2011. Are we ready for a natural history of motor learning? [[Media:Journal_Club_Aug_30_2017.pdf]] [http://www.sciencedirect.com/science/article/pii/S0896627311009299 Paper]
* [Sept 11, 2017] Thura and Cisek, 2017. The Basal Ganglia Do Not Select Reach
Targets but Control the Urgency of Commitment [[File:JC_Sept_11.pdf]]
[https://www.ncbi.nlm.nih.gov/pubmed/28823728 Paper]

Interesting Papers for future Journal Clubs:

Journal Club

2017-09-26T13:38:53Z

Brandon:

Archive of Journal Club Presentations:
* [Aug 30, 2017] Shmuelof and Krakauer, 2011. Are we ready for a natural history of motor learning? [[Media:Journal_Club_Aug_30_2017.pdf]] [http://www.sciencedirect.com/science/article/pii/S0896627311009299 Paper]
* [Sept 11, 2017] Thura and Cisek, 2017. The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment [[File:JC_Sept_11.pdf]]
[https://www.ncbi.nlm.nih.gov/pubmed/28823728 Paper]

Interesting Papers for future Journal Clubs:

Journal Club

2017-09-26T13:38:38Z

Brandon:

Archive of Journal Club Presentations:
* [Aug 30, 2017] Shmuelof and Krakauer, 2011. Are we ready for a natural history of motor learning? [[Media:Journal_Club_Aug_30_2017.pdf]] [http://www.sciencedirect.com/science/article/pii/S0896627311009299 Paper]
* [Sept 11, 2017] Thura and Cisek, 2017. The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment [[File:JC_Sept_11.pdf]]
[https://www.ncbi.nlm.nih.gov/pubmed/28823728]

Interesting Papers for future Journal Clubs:

File:JC Sept 11.pdf

2017-09-26T13:37:51Z

Brandon:

Journal Club

2017-09-26T13:37:12Z

Brandon:

Archive of Journal Club Presentations:
* [Aug 30, 2017] Shmuelof and Krakauer, 2011. Are we ready for a natural history of motor learning? [[Media:Journal_Club_Aug_30_2017.pdf]] [http://www.sciencedirect.com/science/article/pii/S0896627311009299 Paper]
* [Sept 11, 2017] Thura and Cisek, 2017. The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment [[Media:[[File:JC_Sept_11.pdf]]
[https://www.ncbi.nlm.nih.gov/pubmed/28823728]

Interesting Papers for future Journal Clubs:

Useful stuff

2016-11-23T18:56:23Z

Brandon: /* General Math */

Software

2016-09-22T13:15:51Z

Brandon:

This page contains useful information about research software used in the lab.

== General useful software ==
* [http://www.ghisler.com/ Total Commander] (free) - file manager
* [https://winscp.net/eng/index.php WinSCP] (free) - file transfer tool
* [http://www.texniccenter.org/ TeXnicCenter] (free) - LateX editor
* [https://www.mendeley.com/ Mendeley reference manager] (free) - manage references & automatic bibliography generator for MSWord, LibreOffice and BibTeX
* [http://www.seamonkey-project.org/ SeaMonkey] (free) - internet application suite including web editor

== Vector graphics ==
* [http://www.coreldraw.com/ca/ CorelDraw] - ask Gunnar for installation CD
* [https://inkscape.org/en/ Inkscape] (free)

== Statistics ==
* SPSS - general purpose
* [https://www.r-project.org/ R] (free) - general purpose with [http://r4ds.had.co.nz/ great online book]!
* [http://psignifit.sourceforge.net/ psignifit] (free) - psychometric function fitting

== Imaging analysis ==
* [http://www.fil.ion.ucl.ac.uk/spm/ SPM] (free) - general purpose (fMRI oriented)
* [http://www.lcs.poli.usp.br/~baccala/pdc/CRCBrainConnectivity/AsympPDC/ PDC] (free) - partially directed coherence analysis
* [http://www.fieldtriptoolbox.org/ FieldTrip] (free) - general purpose (EEG/MEG oriented)
* [http://cheynelab.utoronto.ca/brainwave Brainwave] (free) and [http://cheynelab.utoronto.ca/httpdoc/Brainwave_v3.1_Documentation_6October_2015_final.pdf documentation] - MEG analysis toolbox
* [http://brainvis.wustl.edu/wiki/index.php/Caret:Download CARET] (free) - anatomical reconstruction toolkit for structural and anatomical data ([http://prefrontal.org/blog/2009/04/using-caret-for-fmri-visualization/ simple tutorial])

== Machine Learning ==
* [http://www.cs.ubc.ca/~murphyk/Software/Kalman/kalman.html Kevin Murphy's Kalman filter toolbox] (free)
*[http://www.csie.ntu.edu.tw/~cjlin/libsvm/oldfiles/index-1.0.html libSVM] - Support Vector Machine Library
*[https://github.com/merwan/ml-class Andrew Ng's ML Programming Exercises]

Software

2016-09-22T13:14:34Z

Brandon: /* Machine Learning */

This page contains useful information about research software used in the lab.

== General useful software ==
* [http://www.ghisler.com/ Total Commander] (free) - file manager
* [https://winscp.net/eng/index.php WinSCP] (free) - file transfer tool
* [http://www.texniccenter.org/ TeXnicCenter] (free) - LateX editor
* [https://www.mendeley.com/ Mendeley reference manager] (free) - manage references & automatic bibliography generator for MSWord, LibreOffice and BibTeX
* [http://www.seamonkey-project.org/ SeaMonkey] (free) - internet application suite including web editor

== Vector graphics ==
* [http://www.coreldraw.com/ca/ CorelDraw] - ask Gunnar for installation CD
* [https://inkscape.org/en/ Inkscape] (free)

== Statistics ==
* SPSS - general purpose
* [https://www.r-project.org/ R] (free) - general purpose with [http://r4ds.had.co.nz/ great online book]!
* [http://psignifit.sourceforge.net/ psignifit] (free) - psychometric function fitting

== Imaging analysis ==
* [http://www.fil.ion.ucl.ac.uk/spm/ SPM] (free) - general purpose (fMRI oriented)
* [http://www.lcs.poli.usp.br/~baccala/pdc/CRCBrainConnectivity/AsympPDC/ PDC] (free) - partially directed coherence analysis
* [http://www.fieldtriptoolbox.org/ FieldTrip] (free) - general purpose (EEG/MEG oriented)
* [http://cheynelab.utoronto.ca/brainwave Brainwave] (free) and [http://cheynelab.utoronto.ca/httpdoc/Brainwave_v3.1_Documentation_6October_2015_final.pdf documentation] - MEG analysis toolbox
* [http://brainvis.wustl.edu/wiki/index.php/Caret:Download CARET] (free) - anatomical reconstruction toolkit for structural and anatomical data ([http://prefrontal.org/blog/2009/04/using-caret-for-fmri-visualization/ simple tutorial])

== Machine Learning ==
* [http://www.cs.ubc.ca/~murphyk/Software/Kalman/kalman.html Kevin Murphy's Kalman filter toolbox] (free)
*[http://www.csie.ntu.edu.tw/~cjlin/libsvm/oldfiles/index-1.0.html libSVM] - Support Vector Machine Library
*[Andrew Ng's Machine Learning Programming Exercises https://github.com/merwan/ml-class]

Useful stuff

2016-09-16T15:54:55Z

Brandon:

Useful stuff

2016-09-16T15:53:25Z

Brandon: /* General Math */

Machine learning

2016-09-14T17:49:33Z

Brandon:

Our Journal Club slides about ML will be posted here.

* [[Media:MLintro.pdf | Machine learning introduction]] - Gunnar
* [[Media:LinearRegression.pdf | Linear Regression]] - Sisi
* [[Media:Linear_Classification.pdf | Linear Classification]] - Parisa
* [[Media:MCMC.pdf | Markov Chain Montre Carlo]] - Gunnar
* [[Media:Intro to PCA and ICA.pdf | Introduction to PCA and ICA]] - Cindy
* [[Media:EM_algorithm.pdf | Expectation Maximization]] - Brandon and Jonathan
* [[Media:HMM-parisa.pdf | Hidden Markov Models]] - Parisa
* [[Media:KalmanFilter.pdf | Kalman filter]] - Josh
* [[Media:ML-ANNs.pdf | Rate-based networks & error back-propagation learning]] - Scott
* [[Media:Support Vector Machines (SVM).pdf | Support Vector Machines]] - Jerry
* [[Media:Deep_Belief_Network_Home_(2).pdf | Deep belief networks ]] - Tiger

----

== Machine learning books ==

* [http://personal.disco.unimib.it/Vanneschi/McGrawHill_-_Machine_Learning_-Tom_Mitchell.pdf Tom Mitchell's book]
* [http://alex.smola.org/drafts/thebook.pdf Smola & Vishwanathan's book]
* [http://ciml.info/dl/v0_8/ciml-v0_8-all.pdf Daume's book]
* [https://www.cs.ubc.ca/~murphyk/MLbook/pml-intro-22may12.pdf Murphy's book]
* [http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf Shalev-Shwartz & Ben-David's book]
* [http://ai.stanford.edu/~nilsson/MLBOOK.pdf Nilsson's book]
* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]
* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]

----

== Online Machine Learning Resources ==
* [https://www.coursera.org/learn/machine-learning ML course by Stanford computer scientist Andrew Ng (requires Coursera signup --> free enrollment)]
*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]
*[http://setosa.io/ev/markov-chains/ Markov Chains explained visually]

Machine learning

2016-09-14T17:48:21Z

Brandon: /* Online Machine Learning Resources */

Our Journal Club slides about ML will be posted here.

* [[Media:MLintro.pdf | Machine learning introduction]] - Gunnar
* [[Media:LinearRegression.pdf | Linear Regression]] - Sisi
* [[Media:Linear_Classification.pdf | Linear Classification]] - Parisa
* [[Media:MCMC.pdf | Markov Chain Montre Carlo]] - Gunnar
* [[Media:Intro to PCA and ICA.pdf | Introduction to PCA and ICA]] - Cindy
* [[Media:EM_algorithm.pdf | Expectation Maximization]] - Brandon and Jonathan
* [[Media:HMM-parisa.pdf | Hidden Markov Models]] - Parisa
* [[Media:KalmanFilter.pdf | Kalman filter]] - Josh
* [[Media:ML-ANNs.pdf | Rate-based networks & error back-propagation learning]] - Scott
* [[Media:Support Vector Machines (SVM).pdf | Support Vector Machines]] - Jerry
* [[Media:Deep_Belief_Network_Home_(2).pdf | Deep belief networks ]] - Tiger

----

== Machine learning books ==

* [http://personal.disco.unimib.it/Vanneschi/McGrawHill_-_Machine_Learning_-Tom_Mitchell.pdf Tom Mitchell's book]
* [http://alex.smola.org/drafts/thebook.pdf Smola & Vishwanathan's book]
* [http://ciml.info/dl/v0_8/ciml-v0_8-all.pdf Daume's book]
* [https://www.cs.ubc.ca/~murphyk/MLbook/pml-intro-22may12.pdf Murphy's book]
* [http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf Shalev-Shwartz & Ben-David's book]
* [http://ai.stanford.edu/~nilsson/MLBOOK.pdf Nilsson's book]
* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]
* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]

----

== Online Machine Learning Resources ==
* [https://www.coursera.org/learn/machine-learning ML online course by Andrew Ng (requires Coursera signup --> free enrollment)]
*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]
*[http://setosa.io/ev/markov-chains/ Markov Chains explained visually]

Machine learning

2016-09-14T17:47:14Z

Brandon:

Our Journal Club slides about ML will be posted here.

* [[Media:MLintro.pdf | Machine learning introduction]] - Gunnar
* [[Media:LinearRegression.pdf | Linear Regression]] - Sisi
* [[Media:Linear_Classification.pdf | Linear Classification]] - Parisa
* [[Media:MCMC.pdf | Markov Chain Montre Carlo]] - Gunnar
* [[Media:Intro to PCA and ICA.pdf | Introduction to PCA and ICA]] - Cindy
* [[Media:EM_algorithm.pdf | Expectation Maximization]] - Brandon and Jonathan
* [[Media:HMM-parisa.pdf | Hidden Markov Models]] - Parisa
* [[Media:KalmanFilter.pdf | Kalman filter]] - Josh
* [[Media:ML-ANNs.pdf | Rate-based networks & error back-propagation learning]] - Scott
* [[Media:Support Vector Machines (SVM).pdf | Support Vector Machines]] - Jerry
* [[Media:Deep_Belief_Network_Home_(2).pdf | Deep belief networks ]] - Tiger

----

== Machine learning books ==

* [http://personal.disco.unimib.it/Vanneschi/McGrawHill_-_Machine_Learning_-Tom_Mitchell.pdf Tom Mitchell's book]
* [http://alex.smola.org/drafts/thebook.pdf Smola & Vishwanathan's book]
* [http://ciml.info/dl/v0_8/ciml-v0_8-all.pdf Daume's book]
* [https://www.cs.ubc.ca/~murphyk/MLbook/pml-intro-22may12.pdf Murphy's book]
* [http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf Shalev-Shwartz & Ben-David's book]
* [http://ai.stanford.edu/~nilsson/MLBOOK.pdf Nilsson's book]
* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]
* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]

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== Online Machine Learning Resources ==
* [https://www.coursera.org/learn/machine-learning ML online course by Andrew Ng (requires Coursera signup --> free enrollment)]
*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]

Useful stuff

2016-09-14T17:30:15Z

Brandon: /* Statistics */