# machine learning
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Classification in Machine Learning - Decision Tree
Brief Summay A supervised learning is a machine learning task of learning a function that maps an input to an output based on example input-output p
Evaluation Metrics in Machine Learning - ROC / AUC
Receiver Operation Curve (ROC) and Area Under Curve (AUC) are important evaluation metrics used in evaluating the performance of the binary classifica
Evaluation Metrics in Machine Learning - F1 Score
F1-score is the weighted average of precision and recall. Hence, since it takes both FP and FN into account, better the balance between precision and
Evaluation Metrics in Machine Learning - Precision / Recall
Precision and Recall are evaluation metrics which emphasize the performance in positive data-set. Precision = (TP) / (TP + FP) ratio of correctly pr
Evaluation Metrics in Machine Learning - Confusion Matrix
Confusion Matrix which is often used as an evaluation metrics in binary classification shows how much the model is confused while performing the predi
Evaluation Metrics in Machine Learning - Accuracy
So far, we have studied various techniques (ex- train/test-split, GridSearchCV, Standardization, Normalization, Data Preprocessing) to enhance our mac
머신러닝? 선형 회귀는 뭐고 비용함수는 무엇인가요?
컴퓨터에 분명하게 프로그래밍되지 않고 스스로 학습할 수 있는 능력을 부여하는 분야이다\- Arthur Samuel수행하는 과제 T와 성능 측정방식 P를 준수하는 경험 E로부터 배우는 컴퓨터 프로그램을 말하며 P에 의해 측정되는 과제 T의 성과가 경험 E에 따라 개선된다
Using Scikit-Learn to Predict Titanic Survivors
Kaggle : Titanic DatasetAs a review, we will be using train.csv from Kaggle's Titanic dataset to predict the survivors from the disaster.Input OutputP
Deep Learning and Machine Learning
Data sets that are so massive, so quickly built, and so varied that hey defy traditional analysis method such as performing with a relational database
#2 Machine Learning : How to minimize Cost
How to minimize Cost > hypothesis > H(x) = Wx Cost(W,b) 수식 > $cost(W,b) = \frac{1}{m} \sum^m_{i=1} (H{x^{(i)}} - y^{(i)})^2$ ⇒* 최소점(minimize
Confusion Matrix for Your Multi-Class Machine Learning Model
Confusion Matrix for Your Multi-Class Machine Learning Model
End to End 머신러닝 프로젝트
큰 그림을 봅니다 (look at the big picture).풀어야할 문제가 무엇인지?지도/비지도/강화학습 중 어떤경우인지분류 또는 회기문제인지배치학습(한꺼번에 학습), 온라인학습(단계적으로 학습)할 것인지이 모델이 전체 시스템안에서 어떻게 사용될지 이해-현재 솔루
Feature Scaling in Scikit Learn
Data Preprocessing is not just about encoding the data and converting the data type within the dataset. It also requires arduous steps to adjust the w