Writing Research Papers in Data Science from Ceni Babaoglu, PhD
Category: ব্লগ । Blog
ব্লগ । Blog
Feb 08
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Principal Component Analysis
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Principal Component Analysis from Ceni Babaoglu, PhD
Feb 08
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagonalization
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagonalization from Ceni Babaoglu, PhD
Feb 08
3. Linear Algebra for Machine Learning: Factorization and Linear Transformations
3. Linear Algebra for Machine Learning: Factorization and Linear Transformations from Ceni Babaoglu, PhD
Feb 08
2. Linear Algebra for Machine Learning: Basis and Dimension
2. Linear Algebra for Machine Learning: Basis and Dimension from Ceni Babaoglu, PhD
Feb 08
1. Linear Algebra for Machine Learning: Linear Systems
1. Linear Algebra for Machine Learning: Linear Systems from Ceni Babaoglu, PhD
Feb 08
Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagonalization
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagonalization from Ceni Babaoglu, PhD
Feb 07
Understanding indicators used to measure health quality
Justetc Social Services (non-profit)Jan 31 · 16 min read This code works with the data on the excel file: indicator-methodology.xls Purpose: Find out prominant indicators — this might also mean the critical aspect of health Find out the measurements that are used to find the quality Code Reference: This code heavily makes use of the code provided on …
Feb 07
Quality of Care, Health System Performance, Canada and Other Countries
Justetc Social Services (non-profit)Jan 31 · 5 min read import pandas as pdimport matplotlib.pyplot as plt%matplotlib inlinefrom __future__ import print_functionfrom ipywidgets import interact, interactive, fixed, interact_manualimport ipywidgets as widgetsquality_of_care = pd.read_excel(‘../data/quality-of-care.xls’)quality_of_care.head() # find all indicatorsquality_of_care.set_index([‘Indicator’])indicators = pd.Index(quality_of_care[‘Indicator’]).unique()# find all yearsyears = quality_of_care[‘Data year’].dropna().unique()indicators[0], years(’30-Day In-Hospital Fatality: AMI’, array([2015, 2014, 2013, ‘Not applicable’, ‘2013’, ‘2014’, ‘2015’, ‘2012 to 2014’, …
