articles-authored's People
articles-authored's Issues
Regularization - HandonML Pg 364
Latex tables/tabularx
CART -> Classification and Regression Tree algorithm
Hands on ML Pg 179
Shell script utilities - Pg 308 & 39
Quick tour of Tensorflow
HandonML Pg 376
Gini index -> maybe overarching category of clustering or decision trees?
Gini -> Handsonml pg 177
entropy -> Handson ml PG 180
Describe Datatable in Markdown
See GKIR and DBCS notebooks
Closures
Team Topologies - Conclusion
Depebdabot configuration
Latex Style Guide
File Structure
00_main.tex
01_preamble.tex
...
00_main.tex
\newcommand{\chptroot}{.}
\newcommand{\lblroot}{dbcs}
\newcommand{\imgsroot}{images}
\newcommand{\rqOneDbcs}{What is the overhead introduced in client projects by \gk?}
\newcommand{\rqTwoDbcs}{Is automated dependency pinning an effective mechanism for resolving \gkirs?}
\newcommand{\rqThreeDbcs}{What are the performed code changes when resolving \gkirs?}
%RQs
\newcommand\rqnumberexistingscore{1\xspace}
\newcommand\rqexistingscore{Does the crowd provide enough support to viably calculate a compatibility score?}
\newcommand\rqnumberconfidenceinterval{3\xspace}
\newcommand\rqconfidenceinterval{How much trust can client developers place in the compatibility score?}
\newcommand\rqnumberothermetrics{2\xspace}
\newcommand\rqothermetrics{Which other sources of information can be considered when the crowd does not provide enough support to calculate a compatibility score?}
\newcommand{\floor}[1]{\lfloor#1\rfloor}
\newcommand{\ceil}[1]{\lceil#1\rceil}
\newcommand{\code}[1]{\texttt{#1}}
\newcommand{\quotes}[1]{``#1''}
\newcommand{\fnu}[1]{\footnote{\url{#1}}}
\newcommand{\gk}{\textsf{Greenkeeper}\xspace}
\newcommand{\npm}{\textsf{npm}\xspace}
\newcommand{\cran}{\textsf{CRAN}\xspace}
\newcommand{\eclipse}{\textsf{Eclipse}\xspace}
\newcommand{\java}{\textsf{Java}\xspace}
\newcommand{\gh}{\textsf{GitHub}\xspace}
\newcommand{\gkir}{GKIR\xspace}
\newcommand{\gkirs}{GKIRs\xspace}
\newcommand{\ir}{IR\xspace}
\newcommand{\irs}{IRs\xspace}
\newcommand{\pr}{PR\xspace}
\newcommand{\prs}{PRs\xspace}
\newcommand{\semver}{SemVer\xspace}
\newcommand{\db}{\textsf{Dependabot}\xspace}
\newcommand{\dbpr}{\db PR\xspace}
\newcommand{\dbprs}{\db \prs}
\newcommand{\cs}{\textsf{Compatibility Score}\xspace}
\newcommand{\checks}{\textsf{Checks}\xspace}
\newcommand{\travis}{\textsf{Travis CI}\xspace}
\newcommand{\ghactions}{\textsf{\gh Actions}\xspace}
\newcommand{\husky}{\textsf{Husky}\xspace}
%Reviewing
\newcommand\ben[1]{\nbc{BEN}{#1}{blue}}
\newcommand\filipe[1]{\nbc{FILIPE}{#1}{purple}}
\newcommand\bram[1]{\nbc{BRAM}{#1}{orange}}
\newcommand\ahmed[1]{\nbc{AH}{#1}{red}}
\input{\chptroot/01_preamble}
%Document
\begin{document}
% \bstctlcite{BSTcontrol}
\input{\chptroot/02_title}
\input{\chptroot/03_authors}
\input{\chptroot/04_abstract}
% Weird IEEE stuff
\maketitle
\IEEEdisplaynontitleabstractindextext
\IEEEpeerreviewmaketitle
%Sections
\input{\chptroot/05_intro}
\input{\chptroot/06_background}
\input{\chptroot/07_data}
\input{\chptroot/08_findings}
\input{\chptroot/09_discussion}
\input{\chptroot/10_related_work}
\input{\chptroot/11_threats}
\input{\chptroot/12_conclusion}
\input{\chptroot/13_acknowledgements}
% \bibliographystyle{IEEEtranN} % basic style, author-year citations
\bibliographystyle{BensIEEEtranN}
\bibliography{dbcs_references.bib}
\newpage
\input{\chptroot/14_bios}
\newpage
\begin{appendices}
\input{\chptroot/99_app_ci_name_regex}
\input{\chptroot/99_app_tuple_datasets}
\input{\chptroot/99_app_ci_calculation}
\end{appendices}
\end{document}
Labeling Style
Sections: \label{\lblroot:findings:existing_score}
Figures: \label{\lblroot:fig:score_distributions}
Package.json & package-lock.json
Principle component analysis
Hands On ML Pg 220
Architecture & System Design
Clean Architecture
Snyk Interview
Residuals, R^2, correlation, linear regression
Progress bars in jupyter
Bonus:
import sys
!{sys.executable} -m pip install ipywidgets
!{sys.executable} -m jupyter labextension install @jupyter-widgets/jupyterlab-manager
from tqdm.notebook import tqdm, trange
import time
use like:
for idx, row in tqdm(df.iterrows())
and
df.progress_apply()
scheduled GH action
Linux directory hierarchy essentials
Pg 42
GH Actions full explanation
- events
- jobs
- runs on
- environments
- secrets
- steps
- uses
- runs
- name
Deep learning network layers
e.g. fully connects, sigmoid function, pooling, convolution
see handsonml pg 460 CNN architectures for a good list
Using jest
things from grokking algorithms
Mean, variance, std dev, std err, confidence interval, confidence level
Call this Exploring Distributions
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