Data Science
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Computer Vision: 객체 트래킹Data Science 2022. 11. 13. 18:24
객체 트래킹 vs 객체 감지 Object Tracking Object detection Shorter time since it's reusing the data (object detection is already completed) longer time to detect since it has to be executed from scratch, frame by frame without reusing data Can be difficult if the object change poses drastically since it only detects an object at the first frame) In every frame, it detects the object again 객체 트래킹 두 가지 알고리즘..
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Machine Learning with Python - ClusteringData Science 2022. 10. 7. 20:27
What is clustering? A group of objects that are similar to other objects in the cluster, and dissimilar to data points in other clusters. Then what is the difference between classification and clustering? The main difference is classification is used for labeled data, whereas clustering is used for non-labeled data(비지도 학습에 주로 사용) Where is clustering used? How can we determine the similarity or d..
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Machine Learning with Python - Classification(작성중)Data Science 2022. 8. 20. 23:01
- What is classification? A supervised approach, categorizing some unknown items into a discrete set of categories of classes - Normally, unlabeled test case 에는 defualt 값을 지정해 0또는 1로 표시한다. -> binary classifier Category가 여럿인 multi-class classification 도 있다 - Classification 의 종류 - K-Nearest Neighbor classification(KNN algorithm) 이란? 인접한 변수끼리 묶어 주는 것 - K-nearest neighbors algorism process 1. Pick a..
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Machine Learning with Python - Regression(Simple, Multiple, Non-linear regression)Data Science 2022. 8. 19. 11:03
Regression: a process of predicting a continuous value Types of regression models: Simple Regression / Multiple Regression Simple Linear Regression: one independent variable(x)을 갖고 하나의 dependent variable(y)을 도출해 내는 것 Multiple Linear Regression: 여러개의 Independent variable 을 갖고 하나의 dependent variable 을 도출해 내는 것 Simple Linear Regression 공식. 세타1은 coefficient 라고 불리고, 쎄타0는 Intercept라고 불린다 How to find t..
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Machine Learning with Python - IntroData Science 2022. 8. 18. 17:50
Python libraries for machine learning Numpy, Pandas, Scikit-learn Scikit-learnd의 기능: preprocessing, model_selection, building classifier, fitting the model, confusion_matrix (결과 출력) Supervised vs Unsupervised learning(지도학습 vs 비지도학습) Supervised model: how to teach? by labeling the dataset Unsupervised learning techniques: Dimension reduction / Density estimation / market basket analysis / Cluster..
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goodFeaturesToTrack method 이용해 코너 검출시 Can't parse 'center'. Sequence item with index 0 has a wrong type 에러Data Science 2022. 8. 14. 14:47
OpenCV - 코너 검출 공부중 다음과 같은 에러가 떴다. 코너 검출은 코너점들이 영상이나 이미지에서 고유한 특징을 갖고 있을 경우 변별력을 두기 위해서다. 이미지 인식 등에 쓰인다. 기존 코드 # 23강 - 코너 검출 import cv2 import numpy as np src = cv2.imread("cup.webp") dst = src.copy() gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY) # 하얀색 객체 검출, 배경은 검은색, 검출하려는 물체는 하얀색으로 변형 corners = cv2.goodFeaturesToTrack(gray, 100, 0.01, 5, blockSize=3, useHarrisDetector=True, k=0.03) # 코너 검출. 코너 품..
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Data Analysis with Python - Module Evaluation & Learning ObjectviesData Science 2022. 8. 13. 18:16
In sample evaluation의 단점: it does not tell us how well the trained model can be used to predict new data Solution? Separate the data to two dataset (Training set, Testing set) First we build our data with training set, then use testing set to assess the our model Training data를 많이 넣을수록 Generalization error 이 발생할 가능성이 높아짐 / 때문에 여러 training data & testing data set를 넣어서 이를 보완한다. 이를 Cross validation..
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Data Analysis with Python - Model DevelopmentData Science 2022. 8. 13. 18:08
A model can be thought of as a mathematical equation used to predict a value given one or more other values More relevant data → more accurate model 3 types of linear Regression Simple linear regression Multiple linear regression Polynomial regression Simple linear regression: The method to help us understand the relationship between two variables Multiple linear regression: The method to help u..