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Interesting SE Links

Just a place to put some links to things I should check out more…

Resources

The No Estimates Movement

http://xprogramming.com/articles/the-noestimates-movement/

https://www.neilkillick.com/blog/noestimates-part-1-doing-scrum-without-estimates

http://agileanswerman.com/no-estimates-does-not-stop-agile-metric-abuse/

http://zuill.us/WoodyZuill/2013/04/25/agile2013-lightning-talk-noestimates/

User Stories and Story Points

http://agilefaq.wordpress.com/2007/11/13/what-is-a-story-point/

Risk Management

https://www.neilkillick.com/blog/noestimates-an-alternative-means-of-risk-management

Languages et al

https://ziglang.org/ a competitor of Rust https://www.rust-lang.org/

https://openjdk.org/

https://openjfx.io/

https://superset.apache.org/ a viz platform

https://www.infoworld.com/article/3709196/the-best-open-source-software-of-2023.html

https://www.infoworld.com/article/3687670/project-valhalla-a-look-inside-javas-epic-refactor.amp.html

https://www.mensurdurakovic.com/hard-to-swallow-truths-they-wont-tell-you-about-software-engineer-job/?utm_source=tldrwebdev

Time Series Analysis

https://wwwmpa.mpa-garching.mpg.de/gadget/gadget2-paper.pdf

https://wwwmpa.mpa-garching.mpg.de/gadget/users-guide.pdf

https://machinelearningmastery.com/time-series-forecasting-methods-in-python-cheat-sheet/

https://pywavelets.readthedocs.io/en/latest/regression/dwt-idwt.html

https://ataspinar.com/2018/12/21/a-guide-for-using-the-wavelet-transform-in-machine-learning/

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2155-9 wavelet-based sequence similarity

http://faculty.washington.edu/dbp/s530/ serious grad-level slides of data analysis

Seasonality Analysis and Forecast in Time Series | by Ayşenur Özen | The Startup | Medium

2.3 Time series patterns | Forecasting: Principles and Practice (2nd ed)

A guide for using the Wavelet Transform in Machine Learning – ML Fundamentals

Long short-term memory - Wikipedia

Autoregressive integrated moving average - Wikipedia

5.8 Nonlinear regression | Forecasting: Principles and Practice (2nd ed)

Characteristics of time series - IBM Documentation

The Wavelet Transform. An Introduction and Example | by Shawhin Talebi | Towards Data Science

Discrete wavelet transform; how to interpret approximation and detail coefficients? - Signal Processing Stack Exchange

python - Normalization of several time-series of different lengths and scale - Stack Overflow

Wavelet‐Based Tests for Comparing Two Time Series with Unequal Lengths - Decowski - 2015 - Journal of Time Series Analysis - Wiley Online Library

Wavelet Analysis - an overview | ScienceDirect Topics

Overview of multilevel wavelet decompositions — PyWavelets Documentation

Time series data characteristics. 3 as-old-as-the-hills characteristics… | by The Nam | Medium

Seasonality - Wikipedia

Chapter 5 Time series regression models | Forecasting: Principles and Practice (2nd ed)

Forecasting: Principles and Practice (2nd ed)

Forecasting: Principles and Practice (3rd ed)

How to Identify and Remove Seasonality from Time Series Data with Python - MachineLearningMastery.com

Chaotic time series prediction using wavelet transform and multi-model hybrid method - Extrica

thjashin/multires-conv: Sequence Modeling with Multiresolution Convolutional Memory (ICML 2023)

SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform | BMC Bioinformatics | Full Text

Wavelet analysis; significance levels; confidence intervals;

Index of /dbp/PDFFILES

https://staff.washington.edu/dbp/

http://faculty.washington.edu/dbp/s519/

Dynamic time warping - Wikipedia

Wavelets:FAQ

11 Classical Time Series Forecasting Methods in Python (Cheat Sheet) - MachineLearningMastery.com

Symmetry | Free Full-Text | Cornish–Fisher-Based Control Charts Inclusive of Skewness and Kurtosis Measures for Monitoring the Mean of a Process

Cornish-Fisher Expansion - Value-at-Risk: Theory and Practice

Cornish-Fisher expansion - Encyclopedia of Mathematics

The Limitations of Cornish-Fisher – MathConsult