Learning Journey

Overview

Welcome to my professional journey!

Focus Areas

1. Time Series Forecasting

Advanced forecasting methodologies.
Statistical analysis and modeling.
Machine learning applications in time series.
Real world implementation cases.

2. Open Source Software Packages

Contributing to community projects.
Package development and maintenance.
Documentation and best practices.
Code quality and testing frameworks.

3. Peer Reviewed Research Articles

Literature review and analysis.
Implementation of research findings.
Critical evaluation of methodologies.
Research-based improvements.

4. Systems Engineering Knowledge

Architecture design patterns.
System integration strategies.
Performance optimization.
Scalability considerations.

Contact

LinkedIn: [https://www.linkedin.com/in/datascientistmk84]
Email: [matthew.kolakowski@yahoo.com]
Twitter: [@MatthewKolakow9]

Last Updated: December 2025

Name		Name	Last commit message	Last commit date
Latest commit History 110 Commits
.github/workflows		.github/workflows
AdventofCode2024		AdventofCode2024
examples		examples
nbs/docs/models		nbs/docs/models
samples		samples
A Fuzzy K-Nearest Neighbor Algorithm.pdf		A Fuzzy K-Nearest Neighbor Algorithm.pdf
A Time Series Analysis-Based Forecasting Framework for the Indian Healthcare Sector.pdf		A Time Series Analysis-Based Forecasting Framework for the Indian Healthcare Sector.pdf
ARXIV_Conformal_Prediction.ipynb		ARXIV_Conformal_Prediction.ipynb
ARXIV_Conformal_Prediction_Revised.ipynb		ARXIV_Conformal_Prediction_Revised.ipynb
ARXIV_Time_Series.ipynb		ARXIV_Time_Series.ipynb
ARXIV_Time_Series_Final.ipynb		ARXIV_Time_Series_Final.ipynb
Bias, Fairness, and Accountability with AI and ML Algorithms.pdf		Bias, Fairness, and Accountability with AI and ML Algorithms.pdf
Cocktails.ipynb		Cocktails.ipynb
Curl.c		Curl.c
Darts Time Series.pdf		Darts Time Series.pdf
Designing Inherently Interpretable Machine Learning Models.pdf		Designing Inherently Interpretable Machine Learning Models.pdf
Discriminatory Analysis. Nonparametric Discrimination- Consistency Properties.pdf		Discriminatory Analysis. Nonparametric Discrimination- Consistency Properties.pdf
DriveOS.drawio		DriveOS.drawio
Forecasting Literature Review.pdf		Forecasting Literature Review.pdf
Fuzzy.pdf		Fuzzy.pdf
Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data.pdf		Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data.pdf
Hierarchical Time Series Forecasting in Emergency Medical Services.pdf		Hierarchical Time Series Forecasting in Emergency Medical Services.pdf
Improving Out of Sample Forecasts With Forecast Reconciliation and Clustering.pdf		Improving Out of Sample Forecasts With Forecast Reconciliation and Clustering.pdf
KnightsTour.py		KnightsTour.py
Logs.py		Logs.py
Low Code AutoML Augmented Data Pipelines.pdf		Low Code AutoML Augmented Data Pipelines.pdf
MAPIE and CREPES.pdf		MAPIE and CREPES.pdf
MAPIE- Open Source Library for Uncertainty Quantification.pdf		MAPIE- Open Source Library for Uncertainty Quantification.pdf
MWIR_Super_Resolution_Mathematical_Recovery_Handout.md		MWIR_Super_Resolution_Mathematical_Recovery_Handout.md
MachineLearningProject.md		MachineLearningProject.md
Midterm Report.drawio		Midterm Report.drawio
Model Selection In Reconciling Hierarchical Time Series.pdf		Model Selection In Reconciling Hierarchical Time Series.pdf
Network.py		Network.py
Pipeline Toolkit for Medical Time Series.pdf		Pipeline Toolkit for Medical Time Series.pdf
Plotly.py		Plotly.py
PyCaret Global Mean Temperature Prediction.pdf		PyCaret Global Mean Temperature Prediction.pdf
PyCaret Prediction of Fraction Unbound in Human Plasma.pdf		PyCaret Prediction of Fraction Unbound in Human Plasma.pdf
README.md		README.md
Ridge Regression- Applications to Nonorthogonal Problems.pdf		Ridge Regression- Applications to Nonorthogonal Problems.pdf
SVG.py		SVG.py
Selecting the Right Time Series Methodology.pdf		Selecting the Right Time Series Methodology.pdf
Self Driving Car.drawio		Self Driving Car.drawio
Simple_Moving_Average.ipynb		Simple_Moving_Average.ipynb
Testing_for_a_Unit_Root_in_a_Time_Series.pdf		Testing_for_a_Unit_Root_in_a_Time_Series.pdf
Tetris.py		Tetris.py
The Data Science Design Manual.pdf		The Data Science Design Manual.pdf
The Harm of Class Imbalance Corections for Risk Prediction.pdf		The Harm of Class Imbalance Corections for Risk Prediction.pdf
UASReport.py		UASReport.py
UseCase.drawio		UseCase.drawio
Why Backtesting Matters and How to Do It Right _ by Davide Burba _ Jul, 2023 _ Towards Data Science.pdf		Why Backtesting Matters and How to Do It Right _ by Davide Burba _ Jul, 2023 _ Towards Data Science.pdf
YOLO_NAS_POSE_Inference_Quick_Start.ipynb		YOLO_NAS_POSE_Inference_Quick_Start.ipynb
advanced-pyspark-for-exploratory-data-analysis.ipynb		advanced-pyspark-for-exploratory-data-analysis.ipynb
arxiv_time_series_data.csv		arxiv_time_series_data.csv
conformal_prediction_data.csv		conformal_prediction_data.csv
conformal_prediction_data_filtered_final.csv		conformal_prediction_data_filtered_final.csv
gpt_online.ipynb		gpt_online.ipynb
network_data.csv		network_data.csv
pong.py		pong.py
robotics_study_guide.md		robotics_study_guide.md
time_series_filtered.csv		time_series_filtered.csv
time_series_filtered.xlsx		time_series_filtered.xlsx
traffic_data.csv		traffic_data.csv

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