- Microsoft AI School is Artificial Intelligence developer education course. After a 5 months programming education, I did team project.
- Period : 2022-09-30 ~ 2023-03-22
- Curriculum : https://msaischool.kr/course | Official Homepage
- Front-End, Python(+PyTorch and etc.) and AI, Machine Learning(+Deep Learning) and additional library, framework.
- LinkedIn, GitHub, Azure Cloud and etc...
- Career Mentoring & Consult, Townhall Meeting and various special lecture of computer science and technology.
- Team project(I did a each 2 of image classification and object detection works)
- This repository is backup space for main class of Microsoft AI School. There are a lot of data about Python, AI script not front end source code.
- Directory : Python Basic
- Learn about basic of Python.
- Python grammer, various library, and etc. script file executed on Google Colab.
- Directory : Aritificial Intelligence Basic
- Practice about Azure Cognitive Services. For example, Computer Vision, Face API, OCR and Custom Vision.
- Useful external library for AI programming. For example, Numpy, Pandas, MatplotLib and etc.
- MySQL, Web Crawling, Data Preprocessing
- Directory : Deep Learning Basic
- Practice about basic of deep learning. For example, scikit-learn, supervised learning(regression, classification), unsupervised learning, tensor, keras, math for CNN and also CNN practice.
- Directory : Cloud Computing
- Practice about cloud computing and deployment of services and container system. For example, Docker, Kubernetes, Azure Machine Learning Studio, Azure - Blog Storage, File Share, Storage Queue, Eventhub, Stream Analytics, Data Studio, IoT Hub(+C# script, do CRUD activity)
- Microsoft Power BI, make a simple chatbot
- Directory : Data Analysis based on Statistics
- Practice about basic data analysis based on statistics used Pandas, Matplotlib and a little bit of Naturl Language Processing.
- Statistics idea of mathmethical elements.
- Directory : Handle Image and Build Dataset
- Practice about handling image and building dataset by using Numpy, OpenCV.
- Directory : Strengthen Data Labeling, Processing Image, Realize Dataset, Data Process Project
- Gather data by using web crawling(Selenium), build custom image dataset, read annotation file(xml, json) and processing to image bounding box, split data for train, validation and test.
- PyTorch start! Build custom dataset class, use augmentation by Albumentation library, process image by keypoints.
- Directory : Artificial Neural Network + Convolutional Neural Network Theory and Practice
- Practice about CNN(Linear Regression, Logistic Regression, Perceptron, ResNet18, 50, RexNet, EfficientNet and various model for custom image dataset classification)
- Directory : Deep Learning and Project for Image Classification Problem Theory and Practice
- Practice about Deep Learning and project for custom image dataset classification problem.
- Rock-Scissor-Paper classify, butterflies, Birds vs Drone, Eastern Asian face classify by age and sex.
- Directory : Object Detection Theory and Practice
- Practice about object detection for custom image and label dataset of object detection.
- Used various models like Fast R-CNN, YOLOv5, YOLOv7 and MMDetection.
- Some of mini projects(Wine Labels Dataset, Animal Dataset, Park Illegal Object Detection)
- Directory : AI Project
- The final AI project.
- Our team made a "Hazardous Flying Object Detection System".
- Our system is based on our classification project.
- Our final object detection system consists on
YOLOv8
+MariaDB
+PyQt5
.