Data Science Club 2019-2020

1. 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.

2. 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!