Foundations

ML Fundamentals

Neural networks, backpropagation, gradient descent — the maths behind AI

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ML Maths Basics
beginner
Manipulate vectors and matrices
Supervised Learning
beginner
Train decision trees, random forests, and neural nets
Unsupervised Learning
intermediate
Apply k-means and DBSCAN clustering
ML Pipelines
intermediate
Engineer features and handle missing data

Showing 542 reads from curated sources

ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
Parameterized Complexity Of Representing Models Of MSO Formulas
arXiv:2604.08707v1 Announce Type: new Abstract: Monadic second order logic (MSO2) plays an important role in parameterized complexity due to the Courcelle's the
Activation Functions Explained: Why ReLU Replaced Sigmoid
Medium · AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Activation Functions Explained: Why ReLU Replaced Sigmoid
The function inside every neuron that makes neural networks actually work and why choosing the wrong one breaks everything. Continue reading on Medium »
Activation Functions Explained: Why ReLU Replaced Sigmoid
Medium · Deep Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Activation Functions Explained: Why ReLU Replaced Sigmoid
The function inside every neuron that makes neural networks actually work and why choosing the wrong one breaks everything. Continue reading on Medium »
Why Hardly Anyone Uses Python’s heapq (But Should)
Medium · Python 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Why Hardly Anyone Uses Python’s heapq (But Should)
You’re probably sorting lists when a heap would solve the problem in a fraction of the time. Here’s what you’re missing. Continue reading on The Python Dispatch
Stop Guessing Staffing Needs: How I’d Predict Daily Museum Visitors Before They Arrive (Part 2)
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Stop Guessing Staffing Needs: How I’d Predict Daily Museum Visitors Before They Arrive (Part 2)
From a trained model in a notebook to a working app that museum/exhibitions/venue operations teams can ACTUALLY use. Continue reading on Medium »
The Most Misunderstood Layer in Enterprise AI: Why Constraints Define Real Decision Systems
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
The Most Misunderstood Layer in Enterprise AI: Why Constraints Define Real Decision Systems
Why 85% of AI pilots fail to scale — and the missing constraints layer that determines whether enterprise AI systems succeed or collapse Continue reading on Med
Bank Reconciliation in Python: Building a Plaid Integration from Scratch
Dev.to · Edwards Tech Innovations 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Bank Reconciliation in Python: Building a Plaid Integration from Scratch
Bank Reconciliation in Python: Building a Plaid Integration from Scratch If you're...
Yapay Zeka Destekli Test Otomasyonunda Temel Metrikler: Entropi, Çapraz Entropi ve Perplexity
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Yapay Zeka Destekli Test Otomasyonunda Temel Metrikler: Entropi, Çapraz Entropi ve Perplexity
Yapay zeka araçlarını test süreçlerimize entegre ederken veya “Niyet Mühendisliği” (Intent Engineering) yaklaşımıyla test senaryoları… Continue reading on Mediu
What an AI Really “Sees” When It Plays a Game
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
What an AI Really “Sees” When It Plays a Game
A clear, rigorous walkthrough of how reinforcement learning converts a world into numbers, actions into value estimates, and experience… Continue reading on Med
Hybrid ML for Market Regime Detection: HMM + K-Means on SPY, IWM, HYG, LQD, VIX
Dev.to · Ayrat Murtazin 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Hybrid ML for Market Regime Detection: HMM + K-Means on SPY, IWM, HYG, LQD, VIX
Combine Hidden Markov Models and K-Means clustering with PCA to detect equity, credit, and volatility regimes in Python.
Dev.to AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Explainable Causal Reinforcement Learning for wildfire evacuation logistics networks in carbon-negative infrastructure
Explainable Causal Reinforcement Learning for wildfire evacuation logistics networks in carbon-negative infrastructure In
I Stopped Watching Tutorials and Built a Fraud Detection System Instead
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
I Stopped Watching Tutorials and Built a Fraud Detection System Instead
From 6.3 million transactions to a real working ML app — my first real data science project Continue reading on Medium »
I Stopped Watching Tutorials and Built a Fraud Detection System Instead
Medium · Data Science 📐 ML Fundamentals ⚡ AI Lesson 1w ago
I Stopped Watching Tutorials and Built a Fraud Detection System Instead
From 6.3 million transactions to a real working ML app — my first real data science project Continue reading on Medium »
I Stopped Watching Tutorials and Built a Fraud Detection System Instead
Medium · Python 📐 ML Fundamentals ⚡ AI Lesson 1w ago
I Stopped Watching Tutorials and Built a Fraud Detection System Instead
From 6.3 million transactions to a real working ML app — my first real data science project Continue reading on Medium »
Beyond Forecasting: Time Series as Reasoning, Not Ritual
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Beyond Forecasting: Time Series as Reasoning, Not Ritual
Time series, causal impact, and the difference between analysis and analysis theater Continue reading on Medium »
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Applying Federated Learning to Financial Services
What is Federated Learning? Continue reading on Medium »
Random Forest Explained: Why One Tree Is Smart, but a Forest Is Safer
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Random Forest Explained: Why One Tree Is Smart, but a Forest Is Safer
How machine learning gets better when it stops trusting a single decision tree Continue reading on Medium »
Random Forest Explained: Why One Tree Is Smart, but a Forest Is Safer
Medium · Data Science 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Random Forest Explained: Why One Tree Is Smart, but a Forest Is Safer
How machine learning gets better when it stops trusting a single decision tree Continue reading on Medium »
Can AI Detect Air Pollution From Space? I Built a Model to Find Out!
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Can AI Detect Air Pollution From Space? I Built a Model to Find Out!
The Problem Isn’t Just Pollution, It’s Measurement Continue reading on Medium »
Dev.to AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Real-time Traffic Accident Risk Prediction based on Frequent Pattern Tree
Medium · LLM 📐 ML Fundamentals ⚡ AI Lesson 1w ago
AI Model Drift — A Silent Killer?
Why models that looked great at launch can quietly become unreliable — and what to do about it. Continue reading on Medium »
When 100% Test Coverage Isn’t Enough
Medium · Data Science 📐 ML Fundamentals ⚡ AI Lesson 1w ago
When 100% Test Coverage Isn’t Enough
Introduction Continue reading on Medium »
Building a Real-Time Face Swap Pipeline in Rust with ONNX Runtime
Dev.to · dd 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Building a Real-Time Face Swap Pipeline in Rust with ONNX Runtime
Most face swap tools are Python scripts stitched together with PyTorch, OpenCV, and a prayer. They...
Medium · Deep Learning 📐 ML Fundamentals 1w ago
Building an End-to-End Student Dropout Prediction ML Pipeline with FastAPI, MLflow, XGBoost, and…
A complete guide to predicting student dropout risk using MLOps best practices Continue reading on Medium »
Medium · Programming 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Answer in 30 sec why every array starts with 0 not 1 in java
Because arrays in Java follow zero-based indexing due to how memory addressing works. Continue reading on Medium »
Java + Spring Boot Blueprint — (Blog 8 Control Flow in Java — How Your Program Starts Thinking)
Medium · Programming 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Java + Spring Boot Blueprint — (Blog 8 Control Flow in Java — How Your Program Starts Thinking)
Learn Control Flow in Java in the simplest way possible. Understand if-else, switch, loops (for, while, do-while), and branching statements Continue reading on
Open-Sourcing the Universe’s Code: One Nanowire, Three Functions, One Density Landscape
Medium · AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Open-Sourcing the Universe’s Code: One Nanowire, Three Functions, One Density Landscape
Fundamental Density Theory (FDT): Dragging Physics Kicking and Screaming Out of a Century-Long Rabbit Hole and Back to Reality. Continue reading on Medium »
How Traditional ML Beats Powerful LLMs at Interpretability
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
How Traditional ML Beats Powerful LLMs at Interpretability
The Day Accuracy Wasn’t Enough Continue reading on Medium »
How Traditional ML Beats Powerful LLMs at Interpretability
Medium · Deep Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
How Traditional ML Beats Powerful LLMs at Interpretability
The Day Accuracy Wasn’t Enough Continue reading on Medium »
How Traditional ML Beats Powerful LLMs at Interpretability
Medium · LLM 📐 ML Fundamentals ⚡ AI Lesson 1w ago
How Traditional ML Beats Powerful LLMs at Interpretability
The Day Accuracy Wasn’t Enough Continue reading on Medium »
Tuning ML hyperparameters with a swarm optimizer inspired by parrot behavior
Dev.to · Vijay Govindaraja 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Tuning ML hyperparameters with a swarm optimizer inspired by parrot behavior
When you train a neural network or any ML model, performance depends heavily on hyperparameters —...
Day 23: Support Vector Machines (SVM) — Finding the Best Boundary
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Day 23: Support Vector Machines (SVM) — Finding the Best Boundary
In Day 23 of my learning journey, I explored Support Vector Machines (SVM), one of the most powerful supervised machine learning… Continue reading on Medium »
Day 23: Support Vector Machines (SVM) — Finding the Best Boundary
Medium · Data Science 📐 ML Fundamentals 1w ago
Day 23: Support Vector Machines (SVM) — Finding the Best Boundary
In Day 23 of my learning journey, I explored Support Vector Machines (SVM), one of the most powerful supervised machine learning… Continue reading on Medium »
One important lesson when building reforestation vs. deforestation monitoring systems
Medium · Python 📐 ML Fundamentals ⚡ AI Lesson 1w ago
One important lesson when building reforestation vs. deforestation monitoring systems
We increasingly recognize the importance of protecting the world’s forest. Continue reading on Medium »
“Mengungkap Sentimen di Instagram”
Medium · Data Science 📐 ML Fundamentals ⚡ AI Lesson 1w ago
“Mengungkap Sentimen di Instagram”
Analisis Hasil Pertandingan Timnas Indonesia di Kualifikasi Piala Dunia dengan Algoritma SVM Continue reading on Medium »
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
GRU in NLP: A Simpler Alternative to LSTM That Still Works Very Well
In a previous NLP series blog, we learned about LSTM and why it became an important sequence model. It was introduced because RNNs… Continue reading on Medium »
Medium · NLP 📐 ML Fundamentals ⚡ AI Lesson 1w ago
GRU in NLP: A Simpler Alternative to LSTM That Still Works Very Well
In a previous NLP series blog, we learned about LSTM and why it became an important sequence model. It was introduced because RNNs… Continue reading on Medium »
When to Use a Tuple vs frozenset in Python ?
Medium · Data Science 📐 ML Fundamentals ⚡ AI Lesson 1w ago
When to Use a Tuple vs frozenset in Python ?
When people first learn Python, tuple often gets introduced as: Continue reading on Medium »
GNN (Graph Neural Networks) Nedir?
Medium · AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
GNN (Graph Neural Networks) Nedir?
Yapay zeka dünyasında “derin öğrenme” denince çoğumuzun aklına ya sıralı metinleri anlayan modeller (ChatGPT gibi) ya da pikselleri analiz… Continue reading on
GNN (Graph Neural Networks) Nedir?
Medium · Deep Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
GNN (Graph Neural Networks) Nedir?
Yapay zeka dünyasında “derin öğrenme” denince çoğumuzun aklına ya sıralı metinleri anlayan modeller (ChatGPT gibi) ya da pikselleri analiz… Continue reading on
PCA Explained Visually in 3D: From Data to Principal Components Step-by-Step
Medium · Data Science 📐 ML Fundamentals ⚡ AI Lesson 1w ago
PCA Explained Visually in 3D: From Data to Principal Components Step-by-Step
Understand the principal component analysis in five steps. Continue reading on Medium »
Dynamic Programming: Solving MDP When You Know the environment rules
Medium · AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Dynamic Programming: Solving MDP When You Know the environment rules
In the last article we built the complete language of reinforcement learning. States, actions, rewards, transitions, value functions, the… Continue reading on M
Medium · Programming 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Mastering Coding Languages: Your Gateway to a Successful Tech Career | AGN HUB
In today’s digital world, coding is more than just a skill — it’s a powerful ability. Whether you want to build websites, create apps, or… Continue reading on M
45 days Python training summer internship with practical training
Medium · Python 📐 ML Fundamentals ⚡ AI Lesson 1w ago
45 days Python training summer internship with practical training
A 45 Days Python Training Summer Internship with Practical Training is one of the best ways to start your journey in programming and… Continue reading on Medium
Choosing the Right Python Data Structure: List, Tuple, Set, or Dictionary?
Medium · Python 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Choosing the Right Python Data Structure: List, Tuple, Set, or Dictionary?
A practical guide to understanding when — and why — to reach for each one. Continue reading on Medium »
The End of Rubbish Pricing: Why Manual Estimates Are Now Obsolete
Medium · Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
The End of Rubbish Pricing: Why Manual Estimates Are Now Obsolete
The current state of waste management is, quite frankly, an environmental and economic embarrassment. Continue reading on Medium »
Dev.to AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
We Hit 99.1% on the LOCOMO Benchmark. Here's How.
We Hit 99.1% on the LOCOMO Benchmark. Here's How. Last week, we hit 99.1% accuracy on the LOCOMO benchmark. For context: Mem0 : 26% Engram : 79.6% Muninn : 99.1
Dev.to AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
QIS vs DiLoCo: Why Google's Distributed Training Breakthrough and Quadratic Intelligence Swarm Solve Completely Different Problems
You are trying to train a large language model across 64 machines without transferring terabytes of gradient data every round. Or you are trying to route what a