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https://numpy.org/doc/stable/reference/random/generated/numpy.random.randint.html?highlight=randint#numpy.random.randint numpy.random.randint — NumPy v1.23 Manual Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned. numpy.org (low, high> 임 원하는 shape를 size로 주고 최대 값과 최소 값을 설정할 수 있다. 예시. 원하는 shape : (2,3,4..

import tensorflow print(tensorflow.__version__)

source: scikit-learn.org/stable/modules/preprocessing_targets.html#preprocessing-targets 6.9. Transforming the prediction target (y) — scikit-learn 0.24.0 documentation 6.9. Transforming the prediction target (y) These are transformers that are not intended to be used on features, only on supervised learning targets. See also Transforming target in regression if you want to transform the predict..

source:scikit-learn.org/stable/modules/generated/sklearn.impute.SimpleImputer.html sklearn.impute.SimpleImputer — scikit-learn 0.24.0 documentation scikit-learn.org class sklearn.impute.SimpleImputer(*, missing_values=nan, strategy='mean', fill_value=None, verbose=0, copy=True, add_indicator=False) Imputation transformer for completing missing values. scikit-learn.org/stable/modules/impute.html#..

class sklearn.ensemble.RandomForestRegressor(n_estimators=100, *, criterion='mse', max_depth=None, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0.0, max_features='auto', max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, bootstrap=True, oob_score=False, n_jobs=None, random_state=None, verbose=0, warm_start=False, ccp_alpha=0.0, max_samples=None) A rando..

source:scikit-learn.org/stable/modules/tree.html#tree 1.10. Decision Trees — scikit-learn 0.24.0 documentation 1.10. Decision Trees Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the scikit-learn.org DesicionTreeR..

source : www.kaggle.com/learn/pandas Learn Pandas Tutorials Solve short hands-on challenges to perfect your data manipulation skills. www.kaggle.com www.kaggle.com/dansbecker/your-first-machine-learning-model Your First Machine Learning Model Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources www.kaggle.com import pandas as pd file_path = '../inpu..

Pandas는 데이터를 받아서 정리할 때 많이 쓰인다. 1. 파일에서 읽어오기 2. 상태 출력하기 import pandas as pd file_path = '../inpuit/data-home/example.csv' my_data = pd.read_csv(file_path) my_data.describe()

출처: tutorialspoint.com Matplotlib - Setting Ticks and Tick Labels - Tutorialspoint Matplotlib - Setting Ticks and Tick Labels Ticks are the markers denoting data points on axes. Matplotlib has so far - in all our previous examples - automatically taken over the task of spacing points on the axis.Matplotlib's default tick locators and for www.tutorialspoint.com Ticks are the markers denoting data..

Numpy 라이브러리에서는 Numpy Array에 한해, 특별한 overloading을 제공한다. 사칙연산 같은 간단한 연산에 사용할 수 있다. C/C++ 에서는 자료형이 다르면 당연히 연산이 불가능하다. // We cannot operate different types under C/C++ int myArray[4] = {1, 2, 3, 4}; int num = 100; // This is an error int newArray = myArray + num Python 에서도 마찬가지이다. 다른 종류의 자료형끼리는 연산이 안된다. myList = [1,2,3,4] num = 100 newList = myList + num # TypeError: can only concatenate list (not "..