Archive for the ‘students’ Category

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Machine Learning Research Tutorials

March 8, 2020

Machine learning has become one of the hottest areas in computer science and technology. Both industry and academia have gone gaga. Big tech companies send 100’s each to the top research conferences and the conference numbers are increasing in size so they are now beyond capacity. But, how do you learn about machine learning in the first place? Assuming you have a strong STEM undergraduate degree and are research savvy, this page points to some appropriate resources for research. These are intended for starting PhD students.

If you are more interested in learning the basics as a potential user, then you will need to find different resources such as the blogs up on https://medium.com/search?q=machinelearning&ref=opensearch or at the MOOCS such as Coursera.

University Classes

Places like Stanford and CMU have very good advanced masters-level classes ideal for starting PhD students. Slides and oftentimes lectures are online for the public. e.g., deep networks for NLP http://web.stanford.edu/class/cs224n/

See also Lex Fridman’s seminars up at https://deeplearning.mit.edu/ . Very good overview of capabilities and directions for a general overview.

Good Venues

Excellent tutorials are available recently at the major conferences, oftentimes with vidoes and/or slides on the website, although sometimes you have to hunt through the author’s webpages. The top conferences include AI&Stats, IJCAI, ICML, ACL … be warned, some tutorials are a bit specialised or advanced.

Machine Learning Summer School (MLSS)

This series is managed by venerable machine learning researchers and only has a few per year internationally. Their list of venues is at http://mlss.cc/ . You have to go to each and navigate disparate and sometimes wacky layouts to locate slides and/or videos.

AutoML

The Freiburg-Hannover group has a great sequence of tutorials on AutoML and learning to learn:

VideoLectures.net

An initiative of the Jozef Stefan Institute, Ljubljana, records many great tutorials, but coverage not as good recently. Go seaching for your favorite subjects:

Others

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Resources for Research Students

March 1, 2020
Monash FIT Postgrad Workshop

On 12th February, Reza Haffari and I organised a workshop to support research students in their journey. It seems our Monash faculty each has their own special superpower, and their quality and relevance blew me away:

  • Maria Garcia De La Banda was a careers expert
  • Christoph Bergmier was an efficiency expert
  • Reza Haffari pondered the big philosophical questions
  • Dinh Phung thought about being the best researcher you could be

Anyway, they presented lots of good material which is on the Monash hard drives. But here I’ve summarised the main resources we all mentioned.

Famous Tutorials/Papers/Books for Research Students

Living productively

(resources from Profs Dinh Phung and Reza Haffari at Monash FIT)

Writing

  • Strunk & White’s “Elements of Style”, a short book summarising good writing, with 5 editions since 1920, considered one of the 100 best English language books ever written, often bought with “On Writing Well”
  • William Zinsser’s “On Writing Well”, a classic guide to writing non-fiction, often bought with Strunk & White
  • Jacque Barzun’s “Simple & Direct”, a writer’s guide, https://www.amazon.com.au/Simple-Direct-Jacques-Barzun/dp/0060937238

Research writing (including for nonnative speakers of English)

(resources from Julie Holden at Monash FIT)

  • Cargill, Margaret, and Patrick O’Connor. Writing scientific research articles: Strategy and steps. John Wiley & Sons, 2013.   ( an updated version is being currently written)
  • Glasman-Deal, H. (2010). Science research writing for non-native speakers of English. London: Imperial College Press. Hargrave-Andrew Library 808.0665 G548S2010 and Monash University Library ebook)
  • Swales, J., and Feak, C. (2012). Academic writing for graduate students: A course for nonnative speakers of English ( 3rd ed.).  Ann Arbor: the University of Michigan Press. (Hargrave-Andrew Library 808.042 S971A 2004)
  • Swales, J., and Feak, C. (2000). English in today’s research world: A writing guide. Ann Arbor: The University of Michigan Press. (Matheson Library 808.042 S971E 2000)
  • Weissberg, R., and Buker, S. (1990). Writing up research: Experimental research report writing for students of English. Englewood Cliffs, NJ: Prentice Hall Regents. (Hargrave-Andrew Library 808.0666 W432W)
  • Graff, G., and Birkenstein, C. (2017). “They say / I say”: The moves that matter in academic writing. New York: Norton & Company. (Caulfield and Matheson Libraries 808.042 G736T 2017).  The full text of the 2010 edition is also available to download at https://www.iss.k12.nc.us/cms/lib/NC01000579/Centricity/Domain/2741/They%20Say%20I%20Say%20Full%20Text.pdf

Resources on quality conferences/journals

Understanding reviewers

The journal editorial process 

(didn’t have “known” resources here, so went Googling … these seemed reasonable)

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Caitie on Einstein A Go Go

October 27, 2019

Caitie and Wray at 3RRR

Caitie Doogan, through her Twitter activies, got invited to talk on a science radio programme on 3RRR:  Einstein A Go Go – 27 October 2019 (our section starts at 25:15 in). Dr Krystal, Dr Ray & Dr Shane were the three scientists asking really relevant questions.  Caitie’s work is at the interface of applications and machine learning, so is far more accessible to the science public.  I came along for the ride, and discussed my work with Turning Point.

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Visiting Zhengzhou University

September 27, 2019

Workshop at Zhengzhou, 2019

Faculty and some students after the workshop, 27/09/19.

Dr. Ming Liu of Deakin organised for Dr. Lan Du and I to give a series of lectures on machine learning and natural language processing at Zhengzhou University in Henan province, from 25-27th September.   I gave versions of some previous talks, as well as presenting a new talk on some of the fundamental principles behind some of the new techniques in deep neural networks like pre-training.

The photo above shows me, with Lan and Ming on my left and Prof. Zan, our principal host, on the right.  Several other Zhengzhou faculty are in the front row and some of the masters + phd students in the back row.   Zhengzhou is a large university with the best students in Henan.  The food was, of course, fabulous.  We had a small dinner with the Dean of the entire Engineering Faculty (seen cut-off, on far left), no less, on Monday night, and I was introduced to the toasting customs of Henan with their tiny 10ml shot glasses!

Dinner at Zhengzhou University

At the faculty club 25/09/19, with the Dean on the far left.  Lan is having his soup and Ming is waving.

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Southeast Asia Machine Learning School

July 9, 2019

Very fortunate to be asked to give a lecture on “Foundations of Supervised Learning” at SEA-MLS in Jakarta on 8th July.  The school was co-organised by Google, so opening talk by Google and a member of the Indonesian government.  A big crowd too!  Everyones slides are up on the schedule page.

Never been to Jakarta so an exciting opportunity meet some colleagues, some students, in a lovely environment. Monash has a school at Malaysia so a few Malaysia Monash folks turned up too.  Here we are after my lecture.

SEAMLS-Monash2

Monash Malaysia and Melbourne students at SEA-MLS.

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Graduating MDS students

May 25, 2018

Our first larger batch of MDS students graduating.   Here are some who attended the ceremony.  Really great students!

MDS_GradMay2018

MDS Graduation May 2018

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Trying out DataCamp this semester

February 21, 2018

Our Master of Data Science students explore a lot of things and discuss.  I got a lot of requests to include the excellent material from DataCamp:

DataCamp logo

DataCamp – who support data science education for free

So we’ll see how it goes.  Not sure how well I’ll get to integrate it, because this semester I’m working more on our introductory statistics class.