Perceptron Challenge: A Practice Project

Once you finish the perceptron training, you have a new challenge to tackle - modifying the

perceptron code to classify a new data set. The information of the data set is listed in the following:

1. No.of classes: 2 (class 0 and 1)
2. No. of training data: 2000
3. No. of testing data: 400
4. No. of features: 3 (feature vector is in 3-dimensional space)
5. Files: training.txt, and testing.txt

Since the original perceptron is only for 2-dimensional data, you need to identify and modify all the dimension-related code to make it work. After you finishing the classification, visualize your training and testing data, and the decision boundary using Grapher in Mac laptop (see example). You can post your results once you finish the project, you can post your results onto the blogger. 

Please feel free to drop by Mr. Lin's office or lab for any questions.

ML Workshop Update

During the ML Workshop last Saturday, four members (Tai Wei, Alan, Jennifer and Crystal) of our research group have been trained to understand perceptron at code level (in C language). They are ready to help other members who are interested in ML go through the learning curve of this basic Artificial Neural Network (ANN) skill. This basic training will form the foundation for the next-level neural network- Multi-layer Perceptron (MLP), which is much more complicated. 

Currently, we are actively exploring the MLP in two Advanced STEM Research projects. One is applying MLP to do regression for the drone position detection; another one is to use MPL to do classification for hand gesture recognition based on EMG signals. Once we understand more about MLP at code level, we will be hosting our next ML Workshop to train our group members. 

In the mean time, any one who missed the last workshop and is interested in learning the perceptron can contact Tai Wei, Alan, Jennifer or Crystal directly to arrange an one-to-one training session (about 1~2 hours). You can also contact me for any training arrangement. We are expecting to use MLP and more advanced algorithms to solve real-world problems.

 

Workshop Resource: Perceptron Code

Please click the following perceptron code including training and classification. There are two project folders:
link to find the

1. PerceptronTrainer: Perform training based on training data in training.txt and save the trained weight at weights.txt.
2. PerceptronClassifier: Perform classification based on the weights.txt and output the result to classification.txt. 

ML Saturday Workshop

Hi All,

We are going to have our ML Workshop from 9:00 am to 4:00 pm this Saturday along with STEM Hackathon in RM 201. The focus will be the hands-on experience of your chosen projects. Each team will be working on your own projects and try to make visible progress in one day. Tutorials will be provided to help you kick start your project. For people who are interested in join one the project but haven't signed up, you can just come in and join a team (see previous post).

Since there will be ACT Test administrated in the school the same day, some of the participants may come after the test. So, when you arrive on Saturday, please go directly to RM 201 (don't go to other test-administrating floors). If you will come late, please email me in advance for lunch arrangement.

You are also encouraged to invite your friend to join the research group. I am looking forward to seeing you this Saturday!