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
All Reads (11,632) Articles (5151)Blog Posts (2352)Tutorials (1029)Research Papers (2742)News (358)
PHP fun: Lean theorem in PHP
Dev.to · david duymelinck 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
PHP fun: Lean theorem in PHP
In following post I saw Designing Reliable Permission Models with Lean 4 ...
Embedding 685 million texts in 32 minutes
Dev.to · Coach Danis 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Embedding 685 million texts in 32 minutes
My embedding pipeline used to take many hours. I'd kick it off, go do other work, come back, find a...
The Feature Store: Consistency and Latency Are Both Non-Negotiable
Dev.to · Ken W Alger 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
The Feature Store: Consistency and Latency Are Both Non-Negotiable
Part 3 of 5 in the series: When Your AI Pipeline Grows Up In the previous post, we worked through...
Overcoming Challenges and Applying Best Practices in Migrating Large JavaScript Codebases to TypeScript
Dev.to · Jeferson Eiji 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Overcoming Challenges and Applying Best Practices in Migrating Large JavaScript Codebases to TypeScript
Explore the major obstacles and effective strategies for transitioning a large JavaScript project to TypeScript with real examples.
LeNet-5: A Visual Guide
Dev.to · Sergiy Bondaryev 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
LeNet-5: A Visual Guide
An interactive guide to the neural network that learned to read handwritten digits. Draw a digit and...
Keyless Deep Learning Steganography: Replacing Spread Spectrum Keys with CNNs 🕵️‍♂️
Dev.to · Anjasfedo 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Keyless Deep Learning Steganography: Replacing Spread Spectrum Keys with CNNs 🕵️‍♂️
Imagine hiding a secret message inside the high-frequency details of an image, transmitting it, and...
The Synthetic Data Trap: When It Helps, When It Lies
Dev.to · The Forward Pass 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
The Synthetic Data Trap: When It Helps, When It Lies
This article originally appeared in The Forward Pass, a weekly newsletter for ML engineers who ship....
Optuna Tutorial: Automate Hyperparameter Tuning for ML Models in Python
Dev.to · pickuma 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Optuna Tutorial: Automate Hyperparameter Tuning for ML Models in Python
How Optuna's define-by-run API, TPE sampler, and pruners automate hyperparameter tuning for scikit-learn, PyTorch, and TensorFlow models, with runnable Python c
Detecting Silent Model Failure: Drift Monitoring That Actually Works
Dev.to · Lukas Brunner 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Detecting Silent Model Failure: Drift Monitoring That Actually Works
TL;DR: Most drift monitoring setups alert on the wrong thing. Feature distribution drift is cheap to...
Part 1: From Model Scores to Business Decisions: Binary Classification, Threshold Tuning, and Real-Time Impact
Dev.to · Shallabh Dixitt 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Part 1: From Model Scores to Business Decisions: Binary Classification, Threshold Tuning, and Real-Time Impact
A practical Python guide to binary classification threshold tuning, business-value evaluation, capacity-aware decision policy, calibration review, and productio
Optimizing Cement Kiln Heat Consumption: A Process Engineer’s Python Approach
Dev.to · Aminuddin M Khan 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Optimizing Cement Kiln Heat Consumption: A Process Engineer’s Python Approach
For over three decades, my world revolved around the deafening roar of industrial fans, the intense...
Cx Dev Log — 2026-05-07
Dev.to · COMMENTERTHE9 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Cx Dev Log — 2026-05-07
JIT Backend: Cracking the Realness Code Back-edge sealing, assert native lowering, and functional...
Your Outlier Detection is Lying to You
Dev.to · Pasquale Molinaro 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Your Outlier Detection is Lying to You
Why DBSCAN breaks in high dimensions and what to do instead You tuned epsilon to 1.5...
Mutation Testing as Architecture Enforcement: Infection in 2026
Dev.to · Gabriel Anhaia 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Mutation Testing as Architecture Enforcement: Infection in 2026
92% coverage means nothing if half your assertions are assertTrue(true). Infection mutates your domain and tells you which tests don't actually test.
The cheapest model call is the one you don't make
Dev.to · Sidharth SP 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
The cheapest model call is the one you don't make
I spent the better part of a week building an alert triage co-pilot, and the most useful thing it...
No Dataset? No Problem. How I Curated a Custom AI Dataset From Instagram & Pinterest to Build a Pose Suggester
Dev.to · SHAIK TAUFEEQ AHMAD 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
No Dataset? No Problem. How I Curated a Custom AI Dataset From Instagram & Pinterest to Build a Pose Suggester
When you start a new Machine Learning project, you pray there’s a clean, ready-to-use dataset on...
Why I Chose Hard Math Over AI for a 38,000 Ticker Financial Engine
Dev.to · Alex Vance 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Why I Chose Hard Math Over AI for a 38,000 Ticker Financial Engine
A technical look at building a deterministic compounding engine with Next.js 15, handling tax-drag logic, and why LLMs are the wrong tool for financial forecast
Beginning a DSA Sheet for Technical Interview Preparation
Dev.to · shipra Shankhwar 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Beginning a DSA Sheet for Technical Interview Preparation
As part of my interview preparation journey, I will be starting a DSA sheet focused on frequently...
Recursion Isn’t Hard. The Call Stack Is Invisible
Dev.to · N Satyadev 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Recursion Isn’t Hard. The Call Stack Is Invisible
Ever went through a simple DFS code and went "I would rather beat an old lady with a stick"? That...
I Built an ML-Powered Email Validation API
Dev.to · Ozhaya 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I Built an ML-Powered Email Validation API
I built an ML model using XGBoost to catch auto-generated disposable emails when blacklists can't...
A Practical Model Selection Matrix for Multi-Model AI Apps
Dev.to · Ye Allen 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
A Practical Model Selection Matrix for Multi-Model AI Apps
When a product starts using more than one AI model, the question changes from "which model is best?"...
Median of Two Sorted Arrays — LeetCode #4 (Hard)
Dev.to · Shubham Gupta 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Median of Two Sorted Arrays — LeetCode #4 (Hard)
Given two sorted arrays, return the median of all their elements combined, in logarithmic time.
Python Sentiment Analysis: From Basics to BERT
Dev.to · MD Shahinur Rahman 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Python Sentiment Analysis: From Basics to BERT
` Imagine opening your laptop and seeing 5,000 product reviews, hundreds of support tickets, and a...
Your benchmarks are lying to you, and your judge is to blame!
Dev.to · Tessl 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Your benchmarks are lying to you, and your judge is to blame!
Last week I published a benchmark comparing six models across eleven agent skills. The numbers in...
Why your diffusion model is slow at batch size 1 (and what actually helps)
Dev.to · Elise Moreau 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Why your diffusion model is slow at batch size 1 (and what actually helps)
TL;DR: Single-image diffusion inference is bottlenecked by kernel launch overhead and attention...
What AI Really Is — From Turing Test to Deep Learning
Dev.to · zeromathai 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
What AI Really Is — From Turing Test to Deep Learning
AI is not just chatbots or neural networks. It is a long-running attempt to answer one...
How RNNs Work — Remembering Previous States in Sequential Data
Dev.to · zeromathai 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
How RNNs Work — Remembering Previous States in Sequential Data
A normal neural network treats each input mostly as a fixed snapshot. But many problems are not...
Class Imbalance — Deep Dive + Problem: Normalize Image
Dev.to · pixelbank dev 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Class Imbalance — Deep Dive + Problem: Normalize Image
A daily deep dive into ml topics, coding problems, and platform features from PixelBank. ...
Creating a super-efficient Valid Palindrome algorithm in C#
Dev.to · Assis Zang 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Creating a super-efficient Valid Palindrome algorithm in C#
First, do you know what a Palindrome is? No? So, according to the first Google result: A palindrome...
What Production ML Systems Taught Me About AI Hallucinations
Dev.to · Mansi Somayajula 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
What Production ML Systems Taught Me About AI Hallucinations
Most discussions about AI hallucinations stay at the chatbot level. “ChatGPT made up a legal...
Predictive operations for BFSI Banking: delay prediction, risk scoring, leakage prevention, and recovery
Dev.to · Ananthapathmanabhan A 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Predictive operations for BFSI Banking: delay prediction, risk scoring, leakage prevention, and recovery
Predictive operations for BFSI Banking: delay prediction, risk scoring, leakage prevention, and...
Is Python High Level Or Low Level?
Dev.to · Aaron Maxwell 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Is Python High Level Or Low Level?
Imagine you need to fill a list with square numbers - or more complex objects, but we'll just use...
Python Logging Levels
Dev.to · Maksym 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Python Logging Levels
Python’s standard logging library uses a numeric severity system to filter log messages. When you set...
Exactly-Once Streaming: Kafka + Flink Best Practices
Dev.to · beefed.ai 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Exactly-Once Streaming: Kafka + Flink Best Practices
Implement exactly-once processing with Kafka and Flink: transactions, checkpointing, idempotent sinks, and testing to prevent duplicates or data loss.
From BASIC to Modern Dev: My Path Into Programming
Dev.to · David Schuster 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
From BASIC to Modern Dev: My Path Into Programming
Programmer, Coder, Developer. I’ve always believed that every developer has an origin story. Some...
Algoverse AI Research: Why the ML Community Calls It a Paper Mill
Dev.to · pickuma 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Algoverse AI Research: Why the ML Community Calls It a Paper Mill
An OpenReview profile with 158 papers and 468 coauthors led r/MachineLearning to expose Algoverse, a paid program selling ML research authorship to high schoole
Scraping dynamic pages with Python, Playwright and AWS Lambda
Dev.to · Łukasz Żmudziński 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Scraping dynamic pages with Python, Playwright and AWS Lambda
A practical guide to scraping dynamic JavaScript-heavy pages with Python, Playwright, and AWS Lambda, then saving scheduled parquet snapshots to S3.
ML-KEM Is Already In Your Browser. Here's How It Actually Works.
Dev.to · Niklas 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
ML-KEM Is Already In Your Browser. Here's How It Actually Works.
A deep-dive into ML-KEM (FIPS 203), the post-quantum key exchange now shipping in Chrome, AWS, and the Linux kernel. Rings, lattices, MLWE, Encaps, Decaps, and
The Boring AI Is the Right AI
Dev.to · André Ahlert 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
The Boring AI Is the Right AI
At the AI Engineer Summit 2025 in New York, the mantra that got repeated from stage after stage was...
Pynsights — The Python Workshop Manual
Dev.to · Marinho 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Pynsights — The Python Workshop Manual
Here is a scenario you probably know. You have been writing Python for a couple of years. You know...
Anatomy of Duck DB for Python Developers
Dev.to · Varun Joshi 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Anatomy of Duck DB for Python Developers
Introduction - SQL without a Server Pandas is widely used for data analysis and almost every data...
Merge Sort vs Bubble Sort — Why 800 Comparisons Beats 147 Every Time
Dev.to · Amar Gul 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Merge Sort vs Bubble Sort — Why 800 Comparisons Beats 147 Every Time
Most developers know Merge Sort is faster than Bubble Sort. But watching it happen makes the...
LeetCode Solution: 20. Valid Parentheses
Dev.to · Vansh Aggarwal 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
LeetCode Solution: 20. Valid Parentheses
The Great Parentheses Puzzle: Cracking LeetCode 20 with Stacks! Hey there, future coding...
I built a fake Google login because my MVP demo could not wait for the OAuth console
Dev.to · Jayant Raj Singh 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I built a fake Google login because my MVP demo could not wait for the OAuth console
I did not set out to build an identity product. I set out to ship a thing with a login button, show...
"One JWT, five services, and the python-jose audience list trap"
Dev.to · Takayuki Kawazoe 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
"One JWT, five services, and the python-jose audience list trap"
audience must be a string or None. That was the exception python-jose threw the moment our unified...
Blocking Secrets Before They Hit the Repository: Building a Pre-Commit Hook With ML
Dev.to · Patience Mpofu 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Blocking Secrets Before They Hit the Repository: Building a Pre-Commit Hook With ML
here are two places you can catch an exposed secret. After it's in the repository — in a CI/CD...
Training on Synthetic Data: How to Build an ML Security Tool Without Touching Real Leaked Secrets
Dev.to · Patience Mpofu 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Training on Synthetic Data: How to Build an ML Security Tool Without Touching Real Leaked Secrets
Before I wrote a single line of model training code, I made a decision that constrained everything...
Why I Chose Random Forest Over Deep Learning for Secrets Detection
Dev.to · Patience Mpofu 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Why I Chose Random Forest Over Deep Learning for Secrets Detection
Every time I mention that my secrets detector uses a Random Forest classifier, someone asks the same...