한국경제신문 with Toss bank MLOps 과정

💡 The difference between an iterable and a scalar data type 💡 Pandas Datetime Module

A special kind of string used in Python to document a module, class, function or method

💡 The difference between Series and DataFrame 💡 The difference between iloc and loc

💡 The difference between Lambda Function and UDF

💡 How to use fig, ax in Matplotlib

💡 The difference between Standard Deviation and Standard Error Standard Deviation Definition A measure of the amount of variation or dispersion in a set of values. Quantify how much the val...

💡 Z-Test and T-Test They are statistical methods used to compare sample data to a population mean or to compare two samples. The choice between a z-test and a t-test depends on the sample size and w...

REGEXP Powerful tools for matching patterns within text

💡 Supervised Learning Provides both problems (features) and answers (labels) to the machine learning model. Classification Definition : Problems predicting Discrete(Categorical) Valued Output Types ...

💡 Cross Validation A technique used to evaluate the performance and generalizability of a machine learning model. Training Set : The subset of the data used to train the model. Validation Set : The...

💡 Data Preprocessing A crucial step that involves transforming raw data into a clean and usable format. Main steps for Data Processing Data Collection Data Cleaning Handling Missing Values: Identi...

💡 Classification Evaluation Accuracy Definition Accuracy = Number of data points with matching predictions / Total number of predictions Accura

💡 Ensemble To obtain more reliable predictions than a single classifier by combining the prediction results of various classifiers 🥨 Voting Combining classifiers with different algorithms Hard Voti...

💡 Regression A technique for modeling the relationship between multiple independent variables (X) and a single dependent variable (y) 🎨 RSS and Gradient Descent RSS A method where the squared error...

💡 Dimensionality Reduction Used to improve model performance or facilitate visualization by removing unnecessary or highly correlated variables while preserving important features of the data 🎨 Cur...

💡 Clustering Group a set of data points into clusters, where points in the same cluster are more similar to each other than to those in other clusters. K-Means Definition : Clustering based on Cent...

💡 Recommendation System A machine learning-based technique that provides optimal suggestions based on user preferences, behavior, and past interaction data 🎨 Collaborative Filtering > Recommendati...

💡 Text Preprocessing The process of converting text data into a format that can be analyzed or processed by a machine learning model 🎨 Corpus > A structured collection of text data that a model can...

💡 Text Mining The process of analyzing text data to extract meaningful information 🎨 Feature Extraction > The process of converting text data into numerical data Bag of Words (BoW) Definition : Re...

💡 Perceptron The basic unit of a neural network, consisting of a single neuron 🎨 Structure of Perceptron Input Layer The input of the perceptron is given in the form of a vector, which can be exp...

💡 Activation Function Transform the output of the neural network non-linearly 🎨 Activation Function Role of the Activation Function Introducing Non-linearity: The neural network can learn complex...

💡Neural Network A machine learning model that mimics the way the human brain processes information 🎨 Batch > A method of dividing the entire dataset into several small groups to solve memory and co...

💡 Backward propagation Algorithm based on the chain rule 🥨 Forward Propagation > Data is propagated from the input layer to the output layer, with calculations occurring at each neuron. Transmissi...

💡 Optimizer An algorithm to minimize the Loss Function 🥨 Gradient Descent Definition: A method to find the minimum value of a given function (usually a Cost function or Loss function) using its gra...

💡 Regularization A method to control model complexity so that the neural network model does not become overly complex 🥨 Overfitting > The phenomenon where a model learns too closely to the training...