Elastic Net Regression: Theory, Geometry, and Numerical Example
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Understand the theory, constraint geometry, and step-by-step numerical calculation of Elastic Net regression.
Categories
Machine learning algorithms
Introduction to Reinforcement Learning (Part 1)
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An intuitive introduction to Reinforcement Learning. Learn the core concepts, Markov Decision Processes, key training trade-offs, and algorithm taxonomies.
Support Vector Machine - Methodology 🧭
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This post explains how Support Vector Machines (SVM and SVR) work, from the hyperplane concept and the kernel trick to the epsilon-insensitive tube used in regression.
Random Forest - Methodology 🌲
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This post explains how Random Forest works, step by step. It covers bootstrap sampling, random feature selection, decision tree growth, and aggregation.
KNN Regression Part 2 – Wind Power Prediction 🌬️⚡
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This post demonstrates how to model wind turbine power using KNN regression with simulated wind-farm data.
K-Nearest Neighbours (KNN) Algorithm - Part 1
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K‑Nearest Neighbors (KNN) is a simple, non‑parametric machine learning algorithm that makes predictions based on the labels of the closest data points in the training set. It is supervised (it needs labeled examples) and can be used for both classification and regression tasks.”
Naive Bayes - Prediction probability Storm days 🌪️
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This is my 1st post about Machine Learning (ML). This is a topic I learnt from the book “An Introduction to Statistical Learning”.
Machine learning projects
Interactive Rubik’s Cube Solver & ML Explainer 🧩
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Learn how to solve a Rubik’s Cube with interactive 3D visualizations, custom algorithms walkthrough, and Python Reinforcement Learning models.
Flappy bird Game Part 2 🐦 with Artificial Neural Network (ANN)
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In this part 2, I will explain a simple Aritifical Neural Network (ANN) model to make Flappy Bird A.I.
Flappy bird Game Part 1 🐦
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In this post, I will guide you through creating a Flappy Bird game, originally developed by Vietnamese creator Dong Ha NGUYEN. In part 2, I will explain a simple Aritifical Neural Network (ANN) model to make Flappy Bird A.I.
densys
Master Thesis: Icing Power Loss Forecasting for Wind Farms in Cold Climates Using Machine Learning
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MSc thesis at rebase.energy (Stockholm): forecasting wind turbine icing power losses at 1-36 hour lead times using SCADA and ERA5-Land data, an extended IEA Wind Task 19 framework, and a two-stage LightGBM classifier-regressor.
Wind Farm Repowering: Veggerslev, Denmark 🇩🇰
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Repowering feasibility study replacing three aging Vestas V44-600 turbines with single modern V82-1.65 MW turbine, achieving 33% energy increase and 38% LCOE reduction.
Techno-Economic Analysis of Biogas-Fed SOFC System for Wastewater Treatment ⚡🔋
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Feasibility study of 120 kW SOFC system achieving 116.88 kW net output with 16.33-year payback for Novara WWTP biogas valorization.
Biomass-to-Liquid Conversion Pathways
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Multi-criteria evaluation and future deployment scenario modeling of biomass-to-liquid (BtL) conversion technologies.
Liège Projects
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Operational planning, sizing, and optimization assignment for Université de Liège; my favorite DENSYS course that sparked my love for programming!
Algae-Based Biofuel for Sustainable Aviation (CBM Module)
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Case-Based Module: Evaluating algae-derived Sustainable Aviation Fuel (SAF) pathways; comprehensive study for aviation decarbonization.