Bletchley Park Day Trip

We are arranging a day trip to Bletchley Park (https://www.bletchleypark.org.uk) during on Friday 8th Nov 2019 (week 6). Bletchley Park is also call Station X, fame as the central site for British (and subsequently, Alliedcodebreakers during World War II, and where  Alan Turing worked as a codebreaker during that time period. The department will pay for the travel and tickets (It will cost you more than £30 if you go there yourself from Reading).

If you are interested please bring a deposit of £10 (to be returned to you on the day of the trip) to room 151 in the Polly Vacher building ASAPThere will be a limited number of seats on the coach and these will be allocated on a first come first served basis.

Data Science Club 2019-2020

Data Science Club meeting
(Spring term 2019/20)

1. The first Data Science Club meeting (Spring term 2019/20)

Welcome to join the Data Science Club of this term.

We will meet this Friday (31 Jan): 1:30-2:30pm, G39 Polly Vacher BuildingIn this Friday’s meeting, we will have:

 1) Video lecture: Introduction to reinforcement learning

 https://www.youtube.com/watch?v=4SLGEq_HZxk

2) Tutorial code: python for reinforcement learning

https://www.learndatasci.com/tutorials/reinforcement-q-learning-scratch-python-openai-gym/

3) Competition registration: SemEval 2020 (NLP and image related) If you are interested, please fill in this formhttps://forms.gle/qKKAvNoriq1yy3cf9 by next Monday.

We are calling for forming teams to patriciate SemEval 2020 competition. http://alt.qcri.org/semeval2020/ . You will need to apply data engineering, data mining, machine learning, AI related techniques to analyse data and build models. You will have a chance to work on a team with undergraduates, master students, phd students, and staff members. You will have a chance to build systems and have publications. (It’s a world-known competition. That’s very good for your CV and career). I will provide supervision and suggestions (As the team leader, my team ranked the 3rd out of 34 teams all around the world on sentiment analysis task 2016).

The timeline is as below:

Competition and Beyond:

19 February 2020: Evaluation start*
11 March 2020: Evaluation end*
18 March 2020: Results posted
17 April 2020: System description paper submissions due
24 April 2020: Task description paper submissions due
10 Jun 2020: Author notifications
1 Jul 2020: Camera ready submissions due
13-14 September 2020:  SemEval 2020

 Please check the home page of SemEval 2020 http://alt.qcri.org/semeval2020/index.php?id=tasks  to see more detailed information about the tasks.

Note that like for all clubs of the department, there is no obligation whatsoever, there is *no formal* membership. You can simply attend the meetings, if you find time!

This club is co-organized by phd student Thanet Markchom thanet.mar@gmail.com

If you have questions or suggestions, please contact me or Thanet.

Data Science Club meeting
(Autumn term 2019/20)

1. The third data science club meeting

will be at 12:30-1:30 Friday (15 Nov), G45.
We will talk about neural networks. Here is the referred material. 
 

2. The second data science club meeting

will be from 12:30- 1:30  Friday (25 Oct), G39 Polly Vacher. We will talk about linear model-part 2: classification.  

Please bring your laptop, install python and sklearn.

  • 1) Video: Please watch these two videos at home:

https://www.youtube.com/watch?v=0kns1gXLYg4

https://www.youtube.com/watch?v=F6GSRDoB-Cg

You are required to do: 
(1) data cleaning: remove Twitter Handles (@user)
(2) tf-idf weighting
(3) logistic regression prediction model
(4) evaluate the accuracy of prediction
 
Please do some work at home. We will only have time to go through the video and tutorial very quickly in the class.

3. The first data science club meeting

was at  12:30- 1:30 Friday(7 Oct). We will talk about linear model.

Please bring your laptop, install python and sklearn.

1) Video lecture: Linear Regression With One Variable (8 minutes): https://www.youtube.com/watch?v=kHwlB_j7Hkc

2) The first machine learning example coding tutorial ( linear regression) https://www.kdnuggets.com/2019/03/beginners-guide-linear-regression-python-scikit-learn.html

For the tutorial: please think about what is the:

–          Input, data type, pre-processing, output?

–          classification model? Math formula, loss function?

–          training, validation, test?

–          Evaluation metrics?

–          Which code lines are related to these?

 3. About Data Science Club

In this club, we define Data Science = creative ideas + data + programming (Machine Learning/Artificial Intelligence/Data Mining/Data Visualization). This club is to help students learn and practice data science skills in a more relaxed, flipped, social, and fun way.

We will organize short video lectureshands-on tutorials, and practice workshops. This club will also support students to form teams to participate data science hackathon or competition events. What you will learn will be useful for any free-form hackathon events, finding a Data Scientist job, or creating your own start-ups.

Example events: Kaggle competitions (https://www.kaggle.com/competitions), Australian government open data hackathon ( https://www.govhack.org/ ).

Everyone is welcome. You don’t need any background knowledge to listen to the video lectures. You might need to have programming background (e.g., python, java) to conduct the tutorial session.

The plan is to have meeting once every 2 weeks. The content covers:

1) Theory: linear model, neural networks, reinforcement learning, generative models, …

2) Application: Chat bots, poem writing program, computer music composer, game play agent, …

Note that like for all clubs of the department, there is no obligation whatsoever, there is *no formal* membership. You can simply attend the meetings, if you find time!

2019 Computer Science Hackathon and Showcase event 

The Department of Computer Science and R. U. Hacking society of University of Reading is proudly bring you a hackathon and showcase event! Welcoming students from all over Thames Valley! Whether you’re completely new to programming or are a seasoned hackathon veteran, you are welcome to join us in this fun and collaborative invention marathon! On Day 1 and 2, you will have a 24 hours student Hackathon event. On Day 3, there will be a team event to analyze a data set, an extreme programming competition, workshop sessions for beginners, and a poster and demo session in the afternoon. Bring your laptops and bright ideas, and we’ll cover food, power and Wi-Fi – beginners welcome!

Day 1, 2: (16, 17 Feb), 24 hours student Hackathon event. Venue: Henley Business School Building. Organised by R. U. Hacking. More details please visit: https://www.ruhacking.me/?no-cache=1

Day 3: (18 Feb) Data Science Hackathon, Competition, and Showcase Event. Venue: Department of Computer Science, Polly Vacher building. Organised by the staff members of the department. We define Data Science Hackathon = creative ideas + data + programming (Machine Learning/Artificial Intelligence/Data Mining/Data Visualization).  Registration: https://goo.gl/forms/7OqIifNCGvcFa3ij2 . More details please visit: http://blogs.reading.ac.uk/computer-science/2019/01/25/data-science-hackathon-and-competition-day/

Prize of Day 3

Track 1

The first prizes: Chiara Zucco  Runner-up: Umarani Ganeshbabu, Bhuvana Dhruva, Ekene Ozioko

Track 3

Best presentation: Andrejus    Runner-up: Ben Magee

Best Video: Group 11 Tarab Shakeb, Sacha Walton     Runner-up: Zixu Guo

Best Poster: James Bradley    Runner-up: Eleni Charalambous

Data Science Hackathon and Competition Day

We are hosting a Data Science Hackathon event from 9:30-16:30 in the Polly Vacher building.  There will be a team event to analyse a data set, an extreme programming competition, workshop sessions for beginners, and a poster and demo session in the afternoon.

Morning Session, 9:30-13:00:

Track 1:  Data Science Hackathon. (You will choose a dataset and form a team to develop any creative software applications based on this dataset. Can form small groups, 3-4 person for one group.)

Track 2: Extreme Programming competition.

Track 3: Tutorial workshop for beginners.

Free lunch 13:00-14:00

Afternoon Session 14:00-15:45:

Track 1: Data Science Hackathon (continued)

Track 4: Poster, system and video demo Session. You can submit the poster and system demo of your Final Year Project, masters or PhD project. You can also submit your video demo from group work in the HCI module.

Prize time 16:15-16:30

Plenty of prizes. A judging panel with academic staff and industry guests will decide the winners of Track 1, 2, and 4. Every track participant will get a small prize.  You have the chance to win £100 or cool stuff with equivalent value for each track (except Track 3).

You can participate or attend one or more tracks. To sign up to attend the event, please fill out the form at:

https://goo.gl/forms/7OqIifNCGvcFa3ij2

 

The MLH Local Hack Day

Reading University Hacking ran a local event as part of Major League Hacking’s Local Hack Day – a global 12-hour hackathon & celebration of learning, building, & sharing on December 1st, 2018. The global sponsors included GitHub, Microsoft and a lot of other swag sponsors and our local partners included the Department of Computer Science at the University of Reading and the Reading University Students’ Union.

We welcomed attendees from all over the surrounding areas, welcoming students from Reading University, Bournemouth University and we even had a young hacker from Maidenhead. All of the attendees were really enthusiastic about attending their first Hackathon and they picked up a lot of new skills throughout the 12-hour event. Our flagship project was a “Live Notification Board for Hackathons” project, powered by the Microsoft Azure cloud platform.

Overall, everyone had an amazing time being part of a global event of over 5,000 attendees and the team at Reading University Hacking are look forward to hosting our flagship 24-hour event in February 2019 at the Henley Business School. More details on the 24-hour event here: https://www.eventbrite.co.uk/e/r-u-hacking-2019-24-hour-student-hackathon-tickets-52684847798

Data Science Hackathon Club Update

  • What we discussed on the first meeting (12/Nov):
  1. Google’s Deep Mind Explained! – Self Learning A.I.
  2. The first machine learning example tutorial (classification) 
  • What we discussed on the second meeting (26 Nov): linear model – part1
  1. Video lecture: linear model
  2. Tutorial problem: write your solution about house price prediction.
  • What we discussed on the third meeting (10 Dec, 11-12, G45): linear model – part2
    1. Video lecture: Gradient Descent, Logistic regression
    2. No practice session due to exam session

Club email list https://hps.vi4io.org/listinfo/data-science-hackathon-club

Inaugural meeting of the Extreme Programming club

Today we met for the Extreme Programming Club for the first time and enjoyed discussing problem solving.

Meeting notes

Introduction

We discussed the importance of programming practice, data structures, and algorithms. Plenty of exercises are available at https://open.kattis.com/

There you can even find a University of Reading Ranklist (so far two students *ever* participated).

Introducing and interactive solving of an easy problem

Firstly, Julian introduced the simple problem here: https://open.kattis.com/problems/modulo

Then we discussed a test harness to automatize the execution of the provided input/output tests to check the correctness of our results using a Bash script.

Then students worked in small groups to discuss the problem and sketch a solution. We then discussed the solution in a bigger group. We discussed the difference of using the data structures array vs. a dictionary to preserve the intermediate results of the computation and also about some performance issues.

Finally, we solved the problem using the programming language C.

Introducing problems for the home challenge

Julian introduced three problems of different complexity challenging students with different experience level.  These problems were:

Easy: https://open.kattis.com/problems/sevenwonders
Medium: https://open.kattis.com/problems/stickysituation
Hard: https://open.kattis.com/problems/marchofpenguins

Note that the hard problem is really hard to be resolved with a performing algorithm.  We briefly discussed the problem descriptions and organized small learning groups to support individual learning.

Next meetings

We discussed during the meeting the organization of subsequent meetings, which will take place Wed. 28th in G43 (likely to move to a different place from there).

About the club:

This is an extracurricular activity that fosters your programming skills and algorithmic thinking, and communication skills regarding programming. These capabilities are often key to yield high-profile jobs from, e.g., Silicon Valley companies like Google.

The club to which everyone – both, little or significant programming skills – is welcome, aims to:

  1. boost your programming confidence
  2. prepare you better for potential future jobs and programming competitions
  3. show that the algorithmic problem solving is fun!