Today I want to learn how to crawl with python. Crawling is one of the ways to collect the data I want from outside. Usually, companies use internal data to analyze, but if they can’t, they have to collect the data themselves from the outside. This is the method used in that case. requests moduleThere …
2021.02.21(pm): Kaggle Loan data binary classification
I’m currently learning R programming, and I’m trying to classify Kaggle loan customers using R programming. The first analysis that can be done using raw data as it is is to estimate (predict, classify) 1 dependent variable with 3 categories using 10 input variables (independent variables, X). Here, the dependent variable (target variable, Y) is …
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2021.01.17(pm): Ensemble – Bagging and Boosting
It’s been a long time since I am back to the machine learning post. Let’s take a look at what I have been dealing with. Supervised learning Supervised learning is to train data using labeled data. Given an input value (X data), it learns the Label (Y data) for the input value and typically has …
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2021.01.16(pm): Prevention of Red Scale Formation during Hot Rolling of Steels
authors : Hikaru Okada, Tomoki Fukagawa, Haruhiko Ishihara, Atsuki Okamoto, Masatoshi Azuma, Yukio Matsuda link : https://doi.org/10.2355/isijinternational.35.886 abstract : Red scale defects usually observed in high Si hot rolled strip were reproduced in a laboratory 3 stand tendem mill. The effects of hot rolling and descaling conditions on the strip surface color and scale structure were examined.Irrespective of Si content …
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2021.01.16(pm): Mechanism of Red Scale Defect Formation in Si-added Hot-rolled Steel Sheets
authors : Tomoki Fukagawa, Hikaru Okada, Yasuhiro Maehara link : 10.2355/isijinternational.34.906 Abstract : The red scale, which is one of the major defects on hot-rolled Si added steel sheets, is reproduced experimentally. On the basis of detailed observation of the scale properties, we propose the mechanism of formation of the red scale. Imcomplete descaling of FeO prior …
2021.01.16(am): Kinetics of High Temperature Oxidation of High Carbon Steels in Multi-component Gases Approximating Industrial Steel Reheat Furnace Atmospheres
authors: H. T. Abuluwefa link: https://www.researchgate.net/publication/286600352_Kinetics_of_High_Temperature_Oxidation_of_High_Carbon_Steels_in_Multi-component_Gases_Approximating_Industrial_Steel_Reheat_Furnace_Atmospheres abstract:The isothermal oxidation behaviour of some carbon steels under various experimental conditions was investigated. The composition of oxidation atmosphere used in this work was chosen to approximate atmospheres found in industrial steel billet reheat furnaces. In order to study the effect of adding each gaseous component in these atmospheres experiments were …
2021.01.10(am): BNN(Bayesian Neural Network)
Machine learning blind spots In 2015, there was a controversy when Google AI recognized black people as gorillas. This shows the blind spot of AI. Humans can distinguish between chicken and poodle, but because the machine separates the image with an algorithm, the pictures below can be recognized as the same picture. Similar examples include …
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2020.10.19(pm): Sum of three different prime numbers
This article was written based on the Sample Problem of YBM COS Pro Level 1 Certification Exam. Problem You want to find a number that represents a number as the sum of 3 different decimals. For example, 33 can be expressed in 4 ways. 3+7+233+11+193+13+175+11+17 Given a natural number n as a parameter, we want …
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2020.08.29(pm): Deep Learning with PYTORCH
I wrote this post with a tutorial on ending deep learning in 60 minutes via the link below.https://tutorials.pytorch.kr/beginner/deep_learning_60min_blitz.html What is PYTORCH? A Python-based scientific computation package targeted at two groups: When computing using GPU is required while replacing NumPy When you need a deep learning research platform that provides maximum flexibility and speed First, let’s …
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2020.08.29(pm): Data Augmentation
This post was written by referring to the contents of a deep learning book from the founder of Keras. : https://www.manning.com/books/deep-learning-with-python Overfitting occurs when there are too few samples to learn. This is because you cannot train a generalizable model on new data. Given a lot of data, the model can learn all possible aspects …