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 (12,348) Articles (5525)Blog Posts (2432)Tutorials (1079)Research Papers (2953)News (359)
Part 4: Edge Deployment of an 86M Parameter Audio Transformer
Dev.to · syamaner 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Part 4: Edge Deployment of an 86M Parameter Audio Transformer
Post 3 ended with three numbers: 97.4% test accuracy, 100% precision, 0 false positives. All of it...
Opus 4.7 vs GLM 5.1: is mixing models worth it?
Dev.to · Edy Silva 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Opus 4.7 vs GLM 5.1: is mixing models worth it?
A couple of months ago, I compared Opus vs GLM by having both of them do a task for me. It’s not that...
Building a Search Engine from Scratch: Lessons from Implementing TF-IDF
Dev.to · diogodls 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building a Search Engine from Scratch: Lessons from Implementing TF-IDF
Over the last month, I’ve been working on a personal project: building a search engine from...
Predicting Telecom Customer Churn with scikit-learn, Keras, and Amazon SageMaker
Dev.to · Tebogo Tseka 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Predicting Telecom Customer Churn with scikit-learn, Keras, and Amazon SageMaker
Predicting Telecom Customer Churn with scikit-learn, Keras, and Amazon SageMaker Every...
Python Roadmap for Beginners in 2026: Skills That Actually Make You Job-Ready
Dev.to · Zestminds Academy 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Python Roadmap for Beginners in 2026: Skills That Actually Make You Job-Ready
Python has been popular for many years, but in 2026, its value for beginners is even...
I built a CLI that hashes your ML accuracy claims before the experiment runs
Dev.to · sk8ordie84 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
I built a CLI that hashes your ML accuracy claims before the experiment runs
I built a CLI that hashes your ML accuracy claims before the experiment runs Last month, a...
Cohere just open-sourced a 5.42 WER speech model - here's what testing it on real audio showed
Dev.to · Jim L 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Cohere just open-sourced a 5.42 WER speech model - here's what testing it on real audio showed
Cohere released their new ASR model on March 26 with a 5.42% Word Error Rate on the LibriSpeech...
I Built a Useless Data Structure in C++17 and Learned More Than Any Tutorial Taught Me
Dev.to · Alex Rosito 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
I Built a Useless Data Structure in C++17 and Learned More Than Any Tutorial Taught Me
I built this because I was bored. No real use case, no production target — just a C++17 exercise to...
Why Data Quality is Becoming More Important Than Model Size in Modern AI Systems
Dev.to · Vishal Uttam Mane 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Why Data Quality is Becoming More Important Than Model Size in Modern AI Systems
For years, progress in artificial intelligence was closely tied to scaling laws, where increasing...
C# 13 vs. F# 8: Functional Programming Performance for .NET 8 Microservices
Dev.to · ANKUSH CHOUDHARY JOHAL 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
C# 13 vs. F# 8: Functional Programming Performance for .NET 8 Microservices
For .NET 8 microservices adopting functional patterns, choosing between C# 13’s new lambda...
How I Built a Real-Time Anomaly Detection Engine for a Cloud Storage Platform
Dev.to · babaolu 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How I Built a Real-Time Anomaly Detection Engine for a Cloud Storage Platform
Introduction Imagine you're running a cloud storage platform — thousands of users...
Recurrent Neural Networks
Dev.to · Akash 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Recurrent Neural Networks
Sequence Processing, POS Tagging, and the Context Problem By the end of this post, the...
How to Migrate a Laravel 11 App to Next.js 15 with TypeScript 5.6 and Prisma 5.20
Dev.to · ANKUSH CHOUDHARY JOHAL 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How to Migrate a Laravel 11 App to Next.js 15 with TypeScript 5.6 and Prisma 5.20
After 14 months of benchmarking 42 production Laravel 11 monoliths, we found that migrating to...
Building a Real‑Time Anomaly Detection Engine for Web Traffic
Dev.to · Patrick Onwujekwe 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building a Real‑Time Anomaly Detection Engine for Web Traffic
Introduction Modern web applications live on the open internet, which means they’re constantly...
How I Built a Real-Time HTTP Traffic Anomaly Detector for a Cloud Storage Platform
Dev.to · Adjerese Precious 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How I Built a Real-Time HTTP Traffic Anomaly Detector for a Cloud Storage Platform
Introduction Imagine you're running a cloud storage platform that serves thousands of...
Real-Time Anomaly Detection Engine for a Cloud Storage Platform
Dev.to · Timilehin Obalereko 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Real-Time Anomaly Detection Engine for a Cloud Storage Platform
I built a Python daemon that watches incoming HTTP traffic in real time, learns what "normal" looks...
🛡️ Building FraudShield: Credit Card Fraud Detection with Imbalanced Data
Dev.to · Mahira Banu 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
🛡️ Building FraudShield: Credit Card Fraud Detection with Imbalanced Data
Fraud detection is one of those problems that looks simple on the surface — classify transactions as...
How Missing Data Analysis Lab uses Flask, Bayesian optimization, and MongoDB in one regression workflow
Dev.to · Sangeeth Macherla 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How Missing Data Analysis Lab uses Flask, Bayesian optimization, and MongoDB in one regression workflow
Missing Data Analysis Lab is a Flask-served Python application for studying missing-value behavior,...
From Pixels to Prescriptions: Engineering OCR Pipelines for Medical Report Simplification Using MongoDB
Dev.to · Kotha Deepak Reddy 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
From Pixels to Prescriptions: Engineering OCR Pipelines for Medical Report Simplification Using MongoDB
Team Members @k_sidharthareddy_15 | @k-deepak-544 | @nupur_madhrey_07 | @avika_kashyap |...
The Sous Chef Who Guesses in Batches
Dev.to · Bongho Tae 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
The Sous Chef Who Guesses in Batches
When Waiting Becomes the Problem You are sitting in a restaurant, watching the kitchen...
Why IoT Data Stumbles Before Fueling Your ML Models
Dev.to · Bernard K 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Why IoT Data Stumbles Before Fueling Your ML Models
Data quality issues in IoT are often a significant challenge in machine learning projects. This is a...
Vesuvius - Recovering Ancient Scrolls with 3D Deep Learning and MongoDB Atlas
Dev.to · Hridya Siddu 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Vesuvius - Recovering Ancient Scrolls with 3D Deep Learning and MongoDB Atlas
Team Members This project was developed by: @sahasra_arsahas — Sahasra Kotagiri @hridya_siddu —...
Automated Model Validation Tests for CI/CD
Dev.to · beefed.ai 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Automated Model Validation Tests for CI/CD
Implement automated validation tests for ML models in CI/CD to catch regressions, data leakage, and drift using MLflow, Deepchecks, and Fairlearn.
Machine Learning Basics for JavaScript Developers
Dev.to · Mahdi BEN RHOUMA 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Machine Learning Basics for JavaScript Developers
A comprehensive guide to understanding machine learning concepts using the language you already know—JavaScript. It's time to bring ML to the browser.
Python Type Hints That Actually Catch Bugs (Not Just Satisfy mypy)
Dev.to · Peyton Green 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Python Type Hints That Actually Catch Bugs (Not Just Satisfy mypy)
Most type hint guides teach you syntax. This one is about which annotations actually prevent...
How to Build a Scalable AI Pipeline
Dev.to · Stefano Di Cecco 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How to Build a Scalable AI Pipeline
🚀 Introduction Building AI systems is easy. Building scalable AI pipelines in production is where...
How I Built a Real-Time Anomaly Detector
Dev.to · Mart Young 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How I Built a Real-Time Anomaly Detector
One quiet evening, a cloud server looked normal on the surface. Users logged in, files moved, and...
Embarquer un modèle ML dans une app mobile offline-first - Architecture et retours d’expérience
Dev.to · Marius 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Embarquer un modèle ML dans une app mobile offline-first - Architecture et retours d’expérience
Le défi Une application mobile qui communique avec un instrument de mesure terrain ,...
Aprendiendo Recurrent Neural Networks (Parte 2): Dándole "memoria" a nuestra red y logrando un MAE de 10.05
Dev.to · galp76 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Aprendiendo Recurrent Neural Networks (Parte 2): Dándole "memoria" a nuestra red y logrando un MAE de 10.05
En la Parte 1 de esta serie, comenzamos nuestro viaje para predecir la falla de turbinas...
Choosing the Right Model (Not the Best One)
Dev.to · Siddhartha Reddy 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Choosing the Right Model (Not the Best One)
The best model is rarely the right model. And chasing it is one of the biggest mistakes in...
Sliding Window in Java: The Trick That Replaces Nested Loops
Dev.to · Quipoin 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Sliding Window in Java: The Trick That Replaces Nested Loops
Many beginners write nested loops for subarray problems. That leads to O(n²) time complexity. But...
#08, It's Not That Hard~ Conditionals and Loops (Chapter 04, Sec 01, 02)
Dev.to · Hanna 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
#08, It's Not That Hard~ Conditionals and Loops (Chapter 04, Sec 01, 02)
Textbook: Self-Study Java (by Shin Yong-kwon) Sections: Chapter 04 Sec 01, Sec 02, Chapter Review...
Demystifying AI for Developers: Beyond the Hype
Dev.to · Matheus 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Demystifying AI for Developers: Beyond the Hype
It's a question that echoes through tech conferences and LinkedIn feeds: "Is AI the future?" For...
🔮 PRISM - AI-Powered Edge Orchestration & Distributed Inference
Dev.to · Francisco Molina 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
🔮 PRISM - AI-Powered Edge Orchestration & Distributed Inference
Deploy ML models at the edge with real-time sync, automatic conflict resolution, and zero...
ML acceleration guide: TPUs vs GPUs
Dev.to · Glen Yu 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
ML acceleration guide: TPUs vs GPUs
There’s a lot of hype around GPUs and NVIDIA, but how much do you know about TPUs? Article...
Chapter 8: RMS Normalisation and Residual Connections
Dev.to · Gary Jackson 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Chapter 8: RMS Normalisation and Residual Connections
Add two stabilisation patterns deep networks need: RMSNorm to keep activations bounded, and residual connections to give gradients a highway.
Machine Learning Driven Crop Yield Prediction with NLP-Based Insight
Dev.to · CHITTIPROLU DAKSHAYANI 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Machine Learning Driven Crop Yield Prediction with NLP-Based Insight
Machine Learning Driven Crop Yield Prediction with NLP-Based Insight is a smart agriculture system....
Tokenizer-Aware Markdown Chunking That Doesn't Shred Tables
Dev.to · Gabriel Anhaia 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Tokenizer-Aware Markdown Chunking That Doesn't Shred Tables
Why fixed 512-token splits cut tables in half, and a Python splitter that respects H2/H3, paragraphs, and sentences with a soft token budget.
Building a Document Processing Pipeline for Legal Translation Workflows
Dev.to · Diogo Heleno 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building a Document Processing Pipeline for Legal Translation Workflows
Building a Document Processing Pipeline for Legal Translation Workflows While working on...
Anomaly Detector
Dev.to · Uchechukwu Enyi 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Anomaly Detector
I Built a Tool That Catches Hackers in Real Time — Here's How It Works Have you ever...
Building Smart Student Engagement Detector: An AI-Powered Early Learning Issue Detection System using ML, NLP & Multimodal Analytics
Dev.to · Srujana Sadhu Sharma 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building Smart Student Engagement Detector: An AI-Powered Early Learning Issue Detection System using ML, NLP & Multimodal Analytics
Team members This project was developed by: Devendhar Rao @devendhar_rao Madhan Chowdary...
Building HyFD: How We Used MongoDB to Store and Analyse Production ML Failure Logs
Dev.to · SOURAB REDDY 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building HyFD: How We Used MongoDB to Store and Analyse Production ML Failure Logs
By @sourab_reddy_ @siddardha796 @bvishnu_2509 @giridhar_58 — developed under the guidance of ...
Building HyFD: How We Used MongoDB to Store and Analyse Production ML Failure Logs
Dev.to · SOURAB REDDY 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building HyFD: How We Used MongoDB to Store and Analyse Production ML Failure Logs
By @sourab_reddy_ @siddardha796 @bvishnu_2509 @giridhar_58 — developed under the guidance of ...
TrustShield AI: Hybrid ML-Based Phishing Detection using Flask, scikit-learn & MongoDB
Dev.to · Yadagani Sai Tejus 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
TrustShield AI: Hybrid ML-Based Phishing Detection using Flask, scikit-learn & MongoDB
The Problem That Made Us Build This Phishing emails are getting much harder to...
My AI Database Just Got Production-Ready: 3 Features That Changed Everything
Dev.to · Charles Wu 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
My AI Database Just Got Production-Ready: 3 Features That Changed Everything
seekdb 1.2.0 isn’t just another version bump. It’s the difference between “cool prototype”...
Building Eignex in the Open
Dev.to · Rasmus Ros 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building Eignex in the Open
I've always been fascinated by applying optimization to solve real-world problems. It is often an...
Why Your Diffusion Model Is Slow at Inference (And It's Not the UNet)
Dev.to · Elise Moreau 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Why Your Diffusion Model Is Slow at Inference (And It's Not the UNet)
TL;DR: Most inference bottlenecks in diffusion pipelines are not in the UNet denoising loop. They are...
Recursion
Dev.to · Monicah Ajeso 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Recursion
A beginner-friendly breakdown of recursion - what it is, how it works, and when to use it, with countdown and factorial examples.