전체 글61 pandas to graph 2019. 9. 16. seaborn 2019. 9. 16. matplotlib 2019. 9. 16. Create a Python Heatmap with Seaborn You can easily create a heatmap using the Seaborn library in Python. For this tutorial, I’m going to create this using Jupyter Notebooks. The first step is to load the dependencies which are the essential library. You can also Learn Python Data Visualization at Code Academy import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt %matplotlib inline Now that we.. 2019. 9. 14. Feature Selection and Feature Extraction in Machine Learning: An Overview Companies have more data than ever, so it’s crucial to ensure that your analytics team is uncovering actionable, rather than interesting data — knowing the difference between Interesting Data and Useful Data. Amongst the important aspects in Machine Learning are “Feature Selection” and “Feature Extraction”. An universal problem of intelligent (learning) agents is where to focus their attention. .. 2019. 9. 14. Whitening Data Whitening은 기본적으로 들어오는 input의 feature들을 uncorrelated 하게 만들어주고, 각각의 variance를 1로 만들어주는 작업이다. 'whiten' data: to normalize each dimension by it's respective standard deviation. -----------------------------------------------------Batch Normalization------------------------------------------------------- 문제는 whitening을 하기 위해서는 covariance matrix의 계산과 inverse의 계산이 필요하기 때문에 계산량이 많을 뿐더러, 설상가상으로 whitening.. 2019. 9. 14. lec0_Feature selection Methods... ----------------------------------------------------------------------------------------------------------------------------------- Filter: Variance / Correlation / Univariate selection * Filter methods: 1. rely on the characteristics of the data (feature characteristics) 2. do not use M.L algorithms 3. model agnostic 4. tend to be less computationally expensive 5. usually give lower .. 2019. 9. 14. Generative VS Discriminative Models Q. There are two images of animal(lion and elephant). Classify it!!! In General, A Discriminative model models the decision boundary between the classes. A Generative Model explicitly models the actual distribution of each class. In final both of them is predicting the conditional probability P(Animal | Features). But Both models learn different probabilities. A Generative Model learns the jo.. 2019. 8. 15. BOJ-2557 https://www.acmicpc.net/problem/2557 print("Hello World!") 2019. 6. 1. Hw2 2018. 4. 21. Lec6 2018. 4. 21. Lec5 2018. 4. 21. 이전 1 2 3 4 5 6 다음
