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Github islr

github islr 9 from ISLR displays four simulations of 100 return vectors from the true (known) distribution of joint returns. I made this penalized_rss() function to compute the penalized sum of squared residuals given a value for the lambda penalty and guesses for beta1 (for Walks) and for beta2 (Assists). This dataset from ISLR shows the wage of some male professionals in the Atlantic US area; along with the wage there are also some “risk factors” for the wage such as health status, education, race. For each date, we have recorded the percentage returns for each of the five previous trading days, Lag1 through Lag5. CASI: A 30,000 foot overview of the past, present, and future of statistics/data science/machine learning. This repository contains Python code for a selection of tables, figures and LAB sections from the book ‘An Introduction to Statistical Learning with Applications in R’ by James, Witten, Hastie, Tibshirani (2013). Part b) If the additional predictors lead to overfitting, the testing RSS could be worse (higher) for the cubic regression fit EXERCISE 4: Plugging in the coefficients, \(\hat Y = 1 + b_1(X) + 3b_2(X)\) \(X < 0: Y = 1 + (0) + 3(0) = 1\) \(0\leq X< 1: 1 + (1) + 3(0) = 2\) \(1\leq X\leq 2: 1 ISLR Unsupervised Learning. Second Edition February 2009 # Packages library (tidyverse) # data manipulation and visualization library (leaps) # model selection functions # Load data and remove rows with missing data (hitters <-na. 1 from ISLR: For each possible model containing a subset of the ten predictors in the Credit data set, the RSS and R2 are displayed. com/lgellis/pixiedust-pixieapp-collegedata The ISLR (Introduction to Statistical Learning with applications in R)  9 Jan 2013 With CLAHub and an open source project on GitHub you can: Sign in with GitHub and create a CLA for your project. R package that helps streamline the workflow of reproducible data analysis, machine learning, and reporting. # Packages library (tidyverse) # data manipulation and visualization library (modelr) # provides easy pipeline modeling functions library (broom) # helps to tidy up model outputs # Load data (default <-as_tibble (ISLR:: Default)) ## # A tibble: 10,000 × 4 ## default student balance income ## <fctr> <fctr> <dbl> <dbl> ## 1 No No 729. My research exists at the intersection of population genetics, quantitative genetics, genomics, and animal breeding; all with the ultimate goal of improving livestock efficiency and sustainability. 3)) trainData <- iris[ind==1,] testData <- iris[ind==2,] Sep 23, 2014 · In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an online course based on their newest textbook, An Introduction to Statistical Learning with Applications in R (ISLR). ISLR: An Introduction to Statistical Learning; by James, Witten, Hastie, Tibshirani (Springer: New York, 2013) DL: Deep Learning by Goodfellow, Bengio and Courville. na (Hitters ISLR Resampling Methods Exercises October 01, 2016 Keeping the streak going but now with exercises from chapter 5 in An Introduction to Statistical Learning with Applications in R. More than 50 million people use GitHub to discover, fork, and contribute to over 100 million projects. We’ll begin discussing \(k\)-nearest neighbors for classification by returning to the Default data from the ISLR package. Predicting a qualitative response for an observation can be referred to as classifying that observation, since it involves assigning the observation to a category, or class. edu/c4x/ I went through the book an Introduction to Statistical Learning by Trevor Hastie, Robert Tibshirani, Daniela Witten, and Gareth James. All the R examples shown in class for Stat 5443 (Computational Statistics) are given below as a list. Some of the codes are my own and the rest are either derived or taken from the R codes are taken from various resources such as matrix examples in R tutorial by Prof. This project is not affiliated with the GitHub company in any way In ISLR: Data for an Introduction to Statistical Learning with Applications in R. com/ZheyuanLi/SplinesUtils (with a PDF version library(SplinesUtils) library(splines) library(ISLR) fit. Pull requests   11 Aug 2018 time with Introduction to Statistical Learning (ISLR) and The Data Science Github Repo: https://github. def show_confusion_matrix(C,class_labels=['0','1']): """ C: ndarray, shape (2,2) as given by scikit-learn confusion_matrix function class_labels: list of Jeremy D. This data set consists of percentage returns for the S&P 500 stock index over 1,250 days, from the beginning of 2001 until the end of 2005. Similar Books: The Elements of Statistical Learning: Data Mining,  I've crowdsourced solutions for ISLR during the online course here: http:// asadoughi. Aug 18, 2020 · New hockeystick package on github The goal of hockeystick is to make essential Climate Change datasets easily available to non-climate experts. Jaeyoon Han on 16 Jan 2016, [ISLR] read ![An Introduction to Statistical Learning with Application in R, G. Embedding an R snippet on your website If a topic in ISLR leaves you curious for more, ESLR is an excellent compliment. Simple linear regression predicts a quantitative response on the basis of a single predictor variable It assumes an approximately linear relationship between and Formally, May 02, 2019 · ISLR documentation built on May 2, 2019, 10:14 a. He found a magazine and wants to know if he can cut out whole words from it and use them to create an untraceable replica of his ransom note. Because this is a linear model, we can dramatically speed up the computation with the formula displayed in section 5. ; countrycode: A package for R which can convert to and from 40+ different country coding schemes, and to 600+ variants of country names in different languages and formats. of 20 variables: ## $ AtBat : int 293 315 479 496 321 594 185 298 323 401 ## $ Hits : int 66 81 130 141 87 169 37 73 81 92 ## $ HmRun : int 1 7 18 20 10 4 1 0 6 17 ## $ Runs : int 30 24 66 65 39 74 23 24 26 49 ## $ RBI : int 29 38 72 78 42 51 8 24 32 66 ## $ Walks : int 14 39 76 37 30 35 21 7 8 65 ## $ Years : int 1 14 3 11 2 11 2 3 2 13 In ISLR: Data for an Introduction to Statistical Learning with Applications in R. Using out-of-state tuition as the response and the other variables as the predictors, perform forward stepwise selection on the training set in order to identify a satisfactory model that uses just a subset of the predictors. omit (ISLR:: Hitters) %>% as_tibble) ## # A tibble: 263 × 20 ## AtBat Hits HmRun Runs RBI Walks Years CAtBat CHits CHmRun CRuns ## * <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> ## 1 315 81 7 24 38 39 2ISLR Book CSE 5334 Saravanan Thirumuruganathan. ISLR Python Codes , [Module Version] [Simulate Misclassification] Scikit Learn [Link] Scikit Image [Link] Scikit Tutorial #1 code Scikit Tutorial #2 code: Overview: ISLR EBook Python GitHub : ISLR: Course PPT R Code : ISLR: Data Read/Write [code] ISLR: Example [data] Q1. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software  Labs from An Introduction to Statistical Learning. The function show_confusion_matrix() we use below is from this blog post by Matt Hancock (with a slight modification). ISLR Resampling Methods Exercises October 01, 2016 Keeping the streak going but now with exercises from chapter 5 in An Introduction to Statistical Learning with Applications in R. test The GitHub version of the package; CRAN packages; The GitHub package is installed from RSPM using install. Course lecture videos from "An Introduction to Statistical Learning with Applications in R" (ISLR), by Trevor Hastie and Rob Tibshirani. In this problem, you will develop a model to predict whether a given car gets high or low gas mileage based on the Auto dataset from the ISLR package. Create a binary variable that takes on a 1 for cars with gas mileage above the median, and a 0 for cars with gas mileage Jan 16, 2016 · [ISLR] Contents. Sep 25, 2014 · There is solution to "Introduction to Statistical Learning" on Amazon , written by the author who wrote the unofficial solutions for "Element of statistical learning&quot;. Are there any other textbooks which could be recommended, either as an alternative to ISLR, or to supplement it? by Gareth James, Daniela Witten Trevor Hastie, and Robert Tibshirani. FCML Ch 4, ISLR Ch 4: 19: W 10/30: Estimation I - Gradient Methods: 20: M 11/4: Estimation II - Laplace Approximation: 21: W 11/6: Estimation III - Sampling, Metropolis-Hastings: 22: M 11/11: Veterans Day: 23: W 11/13: Classification - Bayesian Classifier: FCML Ch 5: 24: M 11/18: Classification - Nearest Neighbors, Classifier Evaluation: 25: W class: center, middle, inverse, title-slide # Optimization ### Machine Learning with R<br> <a href='https://therbootcamp. We consider two strings to be anagrams of each other if the first string’s letters can be rearranged to form the second string. Before moving on to logistic regression, why not plain, old, linear regression? default_trn_lm = default_trn default_tst_lm = default_tst Since linear regression expects a numeric response variable, we coerce the response to be numeric. 079-so the bias is extremely small Still, I wrote up a simple script, seen below, to get two-dimensional partial dependence plots. ISLR ") # To view only datasets in a package (results will open in a new tab): In this lab, we will perform KNN clustering on the Smarket dataset from ISLR. In the context of modeling, the models which we have looked at so far have been single guesses; however, often the underlying process is more complex than any single model can explain. Example: Credit Card Defualt 0 500 1000 1500 2000 2500 0 20000 40000 60000 Balance Income No Yes 0 500 1000 1500 2000 2500 Default Balance No Yes 0 20000 40000 60000 ISLR: Most of my notes center around this text, which is targeted at undergraduates. 248-251 of "Introduction to Statistical Learning with Applications in R" by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. packages("leaflet") # to install the development version from Github, run # devtools::install_github("rstudio/leaflet") Once installed, you can use this package at the R console, within R Markdown documents, and within Shiny applications. An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code - JWarmenhoven/ISLR-python. Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (ISLR) This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4. Apr 13, 2014 · A Solution Manual and Notes for: An Introduction to Statistical Learning: with Applications in R: Machine Learning - Kindle edition by Weatherwax, John. Usage GitHub, make a pull request and fix an issue yourself!This process is partially automated by the edit button in the top-left corner of the html version. islr Data for an Introduction to Statistical Learning with Applications in R We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R'. packages("ISLR") library (ISLR) head (Auto) ## mpg cylinders displacement horsepower weight acceleration year origin ## 1 18 8 307 130 3504 12. pdf ] : the slides may be slightly above that of ISLR [Homework]: ISLR (Print7), Chapter 2: 1, 3, 8, 10. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software  Приложения к книге "Введение в статистическое обучение с примерами на языке R" - ranalytics/islr-ru. If one variable is contains much larger numbers because of the units or range of the variable, it will dominate other variables in the distance measurements. Usage ISLR Python Codes , [Module Version] [Simulate Misclassification] Scikit Learn [Link] Scikit Image [Link] Scikit Tutorial #1 code Scikit Tutorial #2 code: Overview: ISLR EBook Python GitHub : ISLR: Course PPT R Code : ISLR: Data Read/Write [code] ISLR: Example [data] Academia. We will not cover ISLR Chapter 3: Linear Regression in much detail, as that is one of the main topics in 456. Another possible warnings message you may get when interacting with CRAN mirrors is: Warning: unable to access index for repository Which may indicate the selected CRAN repository is currently be unavailable. \end{align} Our plan today In general, when creating predictive models, we are trading o two di erent goals: I On one hand, we want models to t the training data well. 494 ## 5 No No This lab on Model Selection using Validation Sets and Cross-Validation is a Python adaptation of p. We will use the Hitters dataset from the ISLR package to explore two shrinkage methods: ridge and lasso. Jackson, PhD Computer Vision, Machine Learning, Big Data and other pursuits May 02, 2019 · ISLR documentation built on May 2, 2019, 10:14 a. May 11, 2018 · Student Solutions to An Introduction to Statistical Learning with Applications in R - yahwes/ISLR An Introduction to Statistical Learning with Applications in R - rghan/ISLR. Oct 02, 2009 · I am trying to replicate Hastie and Tibshirani's regression tree example using the Hitter data in the ISLR package. Alternatively, the list of available packages can be seen in a browser for CRAN, CRAN (extras), Bioconductor, R-forge, RForge, and github. The data contains 1070 purchases where the customer either purchased Citrus Hill or Minute Maid Orange Juice. ISLR-python This repository contains Python code for a selection of tables, figures <A href='http://nbviewer. Suppose we collect data for a group of students in a statistics class with variables \(X_1\) =hours studied, \(X_2\) =undergrad In ISLR: Data for an Introduction to Statistical Learning with Applications in R. Morgan Stanley Chair in Business Administration, Professor of Data Sciences and Operations Conceptual 1. bookdown:: recreation of ISLR textbook built with bookdown and using modern R code (mostly of the tidyverse::) rportr. (The MIT Press: Cambridge, 2016) Free electronic versions are available (ISLR, DL) or hard copy through Amazon (ISLR, DL). OK — Sign up to my email group below and I’ll send you my free eBook on tips to becoming a (better) data scientist (and signup even if you aren’t interested in the eBook). In this case meaning the model is bad at predicting when the market will go down, doing so at only 54/(430+54) = 11. data (Hitters, package = "ISLR") This dataset has some missing data in the response Salaray. Github Repo See Repo On  An Introduction to Statistical Learning, with Applications in R (ISLR) can be in the following Github repository: https://github. linear_model import LinearRegression from patsy import dmatrix %matplotlib inline GitHub Gist: star and fork niranjv's gists by creating an account on GitHub. While ISLR seems good for a light statistical background of many important topics, there's little to no coverage of things such as neural nets, reinforcement learning, unsupervised learning, etc. spline <- lm(wage  The Mirror Site (1) - GitHub - HTML and PDF (download) · Videos (Lectures and Interviews). My Python code for labs and exercises in the book "An Introduction to Statistical Learning with Applications in R". of each chapter, there is a GitHub repository of solutions provided by  29 Jun 2017 My Tutorial Link: https://github. Whenever I go through a book, I think it’s important to try and tackle the exercises in order to be sure one understands the materials. The lab code is based on the codes provided in the book 'An Introduction to Statistical Learning' . Are there any other textbooks which could be recommended, either as an alternative to ISLR, or to supplement it? Aug 03, 2018 · The code for these z-plots can be found in my Github repo here. ISLR covers a large number of algorithms and techniques such as K-nearest neighbor, K-Mean, Linear Regression, Logistic Regression, LDA, QDA, Ridge Regression, Lasso, Splines, Decision Trees along with Bagging and Boosting, SVM, Hierarchical Clustering. 'An Introduction to Statistical Learning with Applications in R' (ISLR) by James, Witten, Hastie and Tibshirani [1]. Create a training set containing a random sample of 800 observations, and a test set containing the remaining observations. DSCI 552 Syllabus { August 4, 2020 3 Exam Dates: Midterm Exam: Tuesday Oct 13, 12-1:50 AM Final Exam: Tuesday Dec 8, 11:00 AM- 1:00 PM Very Important Note: The MW section of this course will have the same midterm and Exercise 6a. Jun 11, 2018 · The figures, formula and explanation are taken from the book "Introduction to Statistical Learning (ISLR)" Chapter 6 and have been adapted in python Sources: ¶ Introduction to Statistical Learning (ISLR) - Chapter 6 2. We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R'. For each of parts (a) through (d), indicate whether we would generally expect the performance of a flexible statistical learning method to be better or worse than an inflexible method. 0 70 1 ## name ## 1 chevrolet chevelle malibu ## 2 buick skylark 320 EXERCISE 4: Part a) Having more predictors generally means better (lower) RSS on training data. 2 attach(College) train = sample(length(Outstate), length(Outstate # Packages library (tidyverse) # data manipulation and visualization library (MASS) # provides LDA & QDA model functions # Load data (default <-as_tibble (ISLR:: Default)) ## # A tibble: 10,000 × 4 ## default student balance income ## <fctr> <fctr> <dbl> <dbl> ## 1 No No 729. News and World Report's College Data 777 18 1 0 1 0 17 CSV : DOC : ISLR Credit Credit Card Balance Data 400 12 3 0 4 0 8 CSV Orange Juice Data Description. Cobham Advanced Electronic Solutions (CAES), and its subsidiary Cobham Gaisler, a leading provider of advanced electronics for mission critical applications, announced today that an abundance of its radiation hardened (RadHard) and high reliability solutions are assisting in the European Space Agency’s (ESA) Solar 7. If your suggestion or fix becomes part of the book, you will be added to the list at the end of this chapter. Modern classification tasks are often extremely unbalanced - a situation where case-control sampling can be very helpful. Machine Learning II Presentation 1: Mid-Term Review Session ISLR - Section 4, Section 8; Overview of trees PDF; Lecture 1. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software  Notes for ISLR (Introduction of Statistical Learning with R). data_address <-"https://lagunita Preface Statisticallearningreferstoasetoftoolsformodelingandunderstanding complex datasets. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. Sketch the tree corresponding to the partition of the predictor space illustrated in the left-hand panel of Figure 8. io home R language documentation Run R code online Create free R Jupyter Notebooks islr Data for an Introduction to Statistical Learning with Applications in R We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R'. 5 Aug 2019 ISLR system uses Indian Sign Language (ISL) dataset for recognition but suffers public at https://github. 3 A picture is worth a thousand words This question should be answered using the Carseats dataset from the ISLR package. 2016 EU Referendum Vote by Region; Comparisons of hypothetical teaching evaluations by POLS0013 students, 2019-20; Comparisons of the strength of reasons to attend UCL by POLS0013 students, 2019-20 Jul 22, 2017 · The authors of the ISLR book/course use the Hitters data from the ISLR R-package. ISLR: Concepts and Exercises A series of posts comprising the summary and solution of exercises of "An Introduction to Statistical Learning". For slides and video ISLR Solutions to Exercises — student solutions to An Introduction to Statistical Learning with Applications in R; Miscellaneous Coding Notes — git, R, web dev 'tidyr' repo — tidy data frame manipulations 'dplyr' repo — another hadleyverse package We again use the Hitters dataset from the ISLR package to explore another shrinkage method, elastic net, which combines the ridge and lasso methods from the previous chapter. This data set consists of percentage returns for the S&P 500 stock index over 1, 250 days, from the beginning of 2001 until the end of 2005. Sep 18, 2016 · ISLR Linear Regression Exercises September 18, 2016 Currently working on the exercises from chapter 3 in An Introduction to Statistical Learning with Applications in R. An effort was made to detail all the answers and to provide a set of bibliographical references that we found useful. About this Book · R Code for Labs · Data Sets and Figures · ISLR Package · Get the Book · Author Bios · Errata · All Labs · Chapter 2 Lab · Chapter 3 Lab. As a textbook for an introduction to data science through machine learning, there is much to like about ISLR. Getting Help GitHub, make a pull request and fix an issue yourself!This process is partially automated by the edit button in the top-left corner of the html version. Jackson, PhD Computer Vision, Machine Learning, Big Data and other pursuits Share on Twitter Share on Google Share on Facebook Share on Weibo Share on Instapaper ISLR-python. The posts do not serve as the replacement for a thorough reading of the book and are intended for the ones who want to have a quick look at various concepts discussed in it. Week 4, 18-Sep, Lab 3: Rstudio, Git & Teams, See Lab3 in your github team page ISLR Chapter 5 G&H 6-8, See HW4-Team-X in your github team page. Here is the Python code that performs the same calculation for minimum sample size: I can demonstrate that this equation returns a correct answer by running another A/B experiment with the sample size that results from the equation. Machine Learning II Presentation 1: Mid-Term Review Session Preface Statisticallearningreferstoasetoftoolsformodelingandunderstanding complex datasets. Luckily there's various attempts to translate all the ISLR exercises into Python on github[1][2] that I have found immensely useful in understanding implementation ISLR Chapter 4 Amit February 07, 2017. Simple linear regression is a straightforward approach for predicting a quantitative response on the basis of a single predictor variable. Usage In this section, you'll study an example of a binary logistic regression, which you'll tackle with the ISLR package, which will provide you with the data set, and the glm() function, which is generally used to fit generalized linear models, will be used to fit the logistic regression model. Though the data set contains only ten predictors, the x-axis ranges from 1 to 11, ISLR: An Introduction to Statistical Learning by James, Witten, Hastie, Tibshirani (Springer: New York, 2013) DL: Deep Learning by Goodfellow, Bengio and Courville. One of the great aspects of the book is that it is very practical in its approach, focusing much effort into making sure that the reader understands how to actually apply the techniques presented. Exercises Resolutions for the book "Introduction to Statistical Learning with R" - tldrafael/ISLR---Introdution-to-Statistical-Learning. 8] Non-parametric methods seek an estimate of $f$ that gets as close to the data points as possible without being too rough or wiggly. This project is a python adaptation of the lab example in "Introduction to Statistical Learning with Applications in R" by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. hockeystick users can download the latest raw data from authoritative sources as well as view it via pre-def ISLR #8. This repository contains Python code for a selection of tables, figures and LAB sections from the book 'An Introduction to Statistical Learning with Applications in R' by James, Witten, Hastie, Tibshirani (2013). Embedding an R snippet on your website In ISLR: Data for an Introduction to Statistical Learning with Applications in R. In this example, I’m using the College data set found in the ISLR package, which examines the relation between graduation rates and various statistics for US Colleges (N = 777) from the 1995 issue of US News and World Report. ISLR Auto Auto Data Set 392 9 0 0 1 0 8 CSV : DOC : ISLR Caravan The Insurance Company (TIC) Benchmark 5822 86 6 0 1 0 85 CSV : DOC : ISLR Carseats Sales of Child Car Seats 400 11 2 0 3 0 8 CSV : DOC : ISLR College U. io'> Basel R Bootcamp </a> <br> <a Github link to the R package multispeciesPP; Will Fithian and Trevor Hastie. With the explosion of “Big Data” problems, statistical learning has become a very hot field in many scientific areas as well as marketing, finance, and other business disciplines. This assignment uses data from the UC Irvine Machine Learning Repository, a popular repository for machine learning datasets. To perform \(k\)-nearest neighbors for classification, we will use the knn() function from the class package. ISLR = Introduction to Statistical Learning PDS = Python for Data Science (see homepage for links) We will use the Hitters dataset from the ISLR package to explore two shrinkage methods: ridge regression and lasso. ISLR Unsupervised Learning Exercises Nov 19, 2015 · EXERCISE 6: For parametric methods, we make an assumption about the shape of the underlying data, select a model form, and fit the data to our selected form. Create a binary variable, mpg01, that contains a 1 if mpg contains a value above its median, and a 0 if mpg contains a value below its median. It’s a great book that gives simple introductions to a lot of the more basic statistical learning approaches. com/ml874/Data-Science-Cheatsheet  2016년 11월 3일 ISLR Chapter 3 - Linear Regression in Python Linear Regression 내용을 Python (Jupyter Notebook)으로 만든 것을 몇일 전 GitHub에 올렸다. tibble:: as_tibble (Hitters) \begin{align} \mathrm{Var}\big[\hat{f}(x_0)\big] = \mathrm{E}[\hat{f}(x_0)^2] - \mathrm{E}[\hat{f}(x_0)]^2. Introduction to supervised learning; regression and classification; k nearest neighbors methods; similarity in machine learning; bias-variance trade-off; cross-validation; Course Overview, Slides. Is there evidence for non-linear relationships in this data set? Create some informative plots to justify your answer. data (Carseats) summary (Carseats) library (ISLR) library (class) We first load some necessary libraries. Support Vector Machines Jesper Armouti-Hansen University of Cologne January 28, 2019 Jesper Armouti-Hansen 6. We provide the collection of data-sets used in the book 'An Introduction to Statistical  I have published my solutions to the questions on github using bookdown which is a great tool to write up books. Not really interested in the coe cients; more interested in the tted function values at any value x0: Figure 6. The readings on this topic are An Introduction to Statistical Learning with Applications in R (ISLR), sections 2. This is the solutions to the exercises of chapter 10 of the excellent book "Introduction to Statistical Learning". For each date, we have recorded the percentage returns for each of the five previous trading days (Lag1 through Lag5). github islr

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