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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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 …
2020.08.08(pm): MLP example – Predicting house prices
Today, I’m going to cover an example of MLP (Muli-Layer Perceptron). For the concept of MLP, please refer to the article I wrote on December 8, 2019. Today, I am going to focus on practice rather than concept. I want to use Kaggle data, which is famous for its dataset, but I want to use …
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2020.04.26(pm): Gaussian Distribution
The Gaussian distribution is another name for the normal distribution. The Gaussian distribution, widely known in statistics, is a very important concept. Last time, I mentioned the concept of probability and statistics and mentioned the central limit theorem. Let’s look at the central limit theorem again. Central limit theorem The sample data sampled from a …
2020.04.12(pm): Regression Example: Housing price prediction
This is a summary of Deep Learning Chapter4 from the founder of Keras. This time, as an example of a regression problem, we will try to predict the housing price. The data we will use today is the Boston Housing Price Dataset, which estimates the median value of housing prices given data such as crime …
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2020.04.05(pm): Binary Classification – Movie Review Classification
We have a lot to do with binary classification in everyday life. For example, there are dogs and cats, 100 won coins and 500 won coins, and iPhone and Samsung Galaxy phones. This time, I’m going to classify a movie review. Binary classification is considered to be the most widely used in machine learning. Let’s …
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2020.03.21(pm): Support Vector Machine(SVM)
The SVM covered in this post is a supervised learning algorithm for solving classification problems. SVM extends the input data to create more complex models that are not defined as simple hyperplanes. SVM can be applied to both classification and regression. Linear models and nonlinear characteristics Because linear and hyperplanes are not flexible, linear models …
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