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Code&Data Insights
[ Domain 1: Connecting to & Preparing Data ] 1.1 Create live connections and extracts 1) Create a live connection to a data source Live connection : connecting to the data source directly rather than connecting to a copy. ( default in Tableau Desktop ) Extract : the subset of data (that we can use to improve performance or to take advandatage of Tableau functionality not available or supported i..
Hyper parameters Hyper parameters : configuration values used to control and tune the behavior of machine learning algorithms and models. These parameters have a significant impact on the model's training process and performance. => Properly setting hyperparameters can optimize the model's performance and prevent overfitting. => Model Performance Optimization, Preventing Overfitting, Saving Trai..
분류 예측시 confusion matrix로 TN, FN, TP, FP 를 표현 할 수 있음. 앞이 실제 값, 뒤가 예측값!!! ( FN - N 예측값 : Negative) TN - 실제 데이터셋 Negative(0), 예측 값 Negative(0) => True!!! TP - 실제 데이터셋 Positive(1), 예측 값 Positive(1) => True!!! FP - 실제 데이터셋 Negative(0), 예측 값 Positive(1) => False FN - 실제 데이터셋 Positive(1), 예측 값 Negative(0) => False 정확도 Accuracy rate - 예측 결과와 실제 값이 동일한 건수 계산? (TN + TP) / (TN + FN+TP+FP) 정밀도 Precision - 데..
[ K-Fold Cross Validation ] K-Fold Cross Validation : a validation technique used to evaluate the performance of a model. It involves dividing the given dataset into K different subsets (or folds), sequentially using each subset as the validation dataset, and using the remaining subsets as the training dataset. [ Grid Search ] Grid Search : Grid Search method involves training and evaluating the..
[ Dimensionality Reduction ] Feature Selection - a process in machine learning and data analysis where a subset of relevant features (variables or attributes) is selected from a larger set of available features. - to improve the model's performance by reducing overfitting, improving interpretability, and enhancing computational efficiency. Feature Extraction - a process in machine learning and d..
Neural Networks Neural Network : A neural network is composed of neurons that take inputs and calculate outputs through weights and activation functions. Through this process, it learns patterns in data and gains the ability to make predictions. Learning in Neural Network 1) Feed Forward 2) Compute Loss 3) Backpropagate ( = chain rule) : the method to compute the gradient efficiently 4) Gradient..
[ Natural Language Processing(NLP) ] Natural Language Processing(NLP) : Natural Language Processing involves the development of algorithms and models that allow computers to comprehend, generate, and interpret sentences, as well as extract meaning from text. => NLP Process (1) text data is collected and preprocessed. During this stage, the text is segmented into sentences or words through tokeni..
[ Reinforcement Learning ] Reinforcement Learning : reinforcement learning is a field of machine learning where a computer program, known as an agent, learns and improves gradually through experience while performing tasks in a specific environment. => Agent interacts with the environment, perceives its current state, selects and executes actions, and receives rewards. => During this learning pr..