Greetings, My name is Sawit Koseeyaumporn ⛹️♂️ . You can call me "Folk"!
Welcome to my learning journey in E-SAN Coding Thailand Season 2 Level 2. (ETPCA SS2)
The content in this repository is about the Personal AI track. By including 6 courses in PowerClass!
Sorry for my bad English. I just want to share knowledges to people around the world from my learning pathway! 💌
- The "Note" is the lecture that I take note of each courses.
- The "Document" is the link to the learning presentation and materials of each courses.
- The "Certificate" is the link to the PowerClass Certification of mine.
You can find the resources from this link here : 🥇 Resources
| Course | Note | Document | Certificate |
|---|---|---|---|
| xPore: An AI-Powered App for Bioinformaticians | 📓 Lecture | 📘 Drive | 🎖️ Certificate |
| Learning from Biosignal | 📓 Lecture | 📘 Drive | 🎖️ Certificate |
| AI for detecting code plagiarism | 📓 Lecture | 📘 Drive | 🎖️ Certificate |
| BiTNet: AI for diagnosing ultrasound image | 📓 Lecture | 📘 Drive | 🎖️ Certificate |
| Mental disorder detection from social media data | 📓 Lecture | 📘 Drive | 🎖️ Certificate |
| AI for arresting criminals | 📓 Lecture | 📘 Drive | 🎖️ Certificate |
- xPore: An AI-Powered APp for Bioinformaticians. ☣️
The course is about the Machine Learning model using Gaussian Mixture Model to match the RNA Sequence and find the M6A sequence (it's the RNA modification and we need to find the pattern in the long RNA sequence)
- Learning from Biosignal 🛌
The course is about the Sleep Stage Analyze by using the Biosignal from our body such as EEG (Brain Wave) and moreover. After we get the Time Series data we use Multi-classification Deep Learning model to detect the pattern of the Sleep stage for each period (30 seconds) in this course we have "DeepSleepNet" and "TinySleepNet" which is the mixture of CNN and RNN architecture in it.
- Merry : Code Clone Detection Model 👽
The course is about the Code clone detection for professor in university to detect the student who copied code from their friends. We use Synthetic Code Metric from Code2Vec to have the similarity vector and then use the cosine similarity to calculate the diff of code. While, we use Semantic Code Metric from ANTLR to tokenize and get the context such as from variables and line of code.
Finally, we combine the Synthetic and Semantic Code Metric and use Machine Learning Model such as Decision Tree, Random Forest, SVM, SVM SMO to classify the type of code clone.
- BitNet : AI for diagnosing ultrasound image 🧑⚕️
The course is about the CNN model to classify the ultrasound image to detect the CCA. We use the pretrained-model called EfficientNet and fine-tuning the model with our own datasets.
This project is made efficiency in term of detection for the doctors.
You can find the workshop references here : https://kku.world/pmubbitnet
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Mental Disorder Detection with Text Classification ⚽ The course is about the NLP (Natural Linguistic Processing) with the techniques called "Text Classification" which is the supervised learning. We use the texts from the social medias to classify whether that people have the diagnose about the depression to the early detection and can let the doctor handles in real soon.
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AI for arresting criminals 👮♂️ The course is about the Object detection using YOLO and detecting the arresting criminals with Roboflow for preprocessing and augmentating the images.