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 (11,570) Articles (5112)Blog Posts (2348)Tutorials (1012)Research Papers (2740)News (358)
Quick Tip: Benchmarking Multimodal APIs in Under 10 Minutes
Dev.to · RileyKim 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Quick Tip: Benchmarking Multimodal APIs in Under 10 Minutes
Look, I’m a backend engineer. I don’t have time to read through 40 pages of model cards before...
I Built a Diagnostic Toolkit for PyTorch Because I Was Tired of Guessing Why Models Fail
Dev.to · Aditya Mehra 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I Built a Diagnostic Toolkit for PyTorch Because I Was Tired of Guessing Why Models Fail
Every time a PyTorch model refuses to learn, the debugging process looks the same: Stare at the...
Similarity Search for Failure Diagnosis
Dev.to · Pedro Santos 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Similarity Search for Failure Diagnosis
Similarity Search for Failure Diagnosis In the previous post, I showed how every saga...
Python Week 3: We Stopped Repeating Ourselves (Loops!)
Dev.to · Navas Herbert 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Python Week 3: We Stopped Repeating Ourselves (Loops!)
I started this session with a challenge. "Jose," I said, "print the names of all 40 students in...
I Built a Multilingual Spam Detection Dataset with 149K+ Messages Across 23 Languages
Dev.to · Arjun M 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I Built a Multilingual Spam Detection Dataset with 149K+ Messages Across 23 Languages
Spam detection datasets are surprisingly bad once you move outside English. Most public datasets...
Construyendo un recomendador de películas en Python: de los datos al modelo
Dev.to · Alberto Martinez 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Construyendo un recomendador de películas en Python: de los datos al modelo
Introducción Los sistemas de recomendación están presentes en muchas plataformas...
Why MLFQ Was Way Ahead of Its Time
Dev.to · N Satyadev 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Why MLFQ Was Way Ahead of Its Time
Enough with the unga bunga puny algorithms.. did you know there exists an scheduling algorithm that...
I'm not an ML engineer. I built one anyway.
Dev.to · Mohamed Zrouga 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I'm not an ML engineer. I built one anyway.
Not because I wanted to — but because every tool I tried on ARM edge devices either needed the cloud,...
Python as a JavaScript Dev
Dev.to · dzaeltic 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Python as a JavaScript Dev
This blog is an introduction to Python, and it assumes that you have a good knowledge of JavaScript...
Inference Is Becoming the New Steady-State Cost Center
Dev.to · NTCTech 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Inference Is Becoming the New Steady-State Cost Center
Training was a bounded investment event. Inference is an unbounded operational residency...
BeautifulSoup and Requests for Web Scraping With Python: When Simple Still Works
Dev.to · Annabelle 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
BeautifulSoup and Requests for Web Scraping With Python: When Simple Still Works
Not every data collection workflow requires browser automation or complex network impersonation. For...
Quantising event-camera networks to run under 1MB on a Cortex-M7
Dev.to · Marco Rinaldi 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Quantising event-camera networks to run under 1MB on a Cortex-M7
TL;DR: I shrunk a gesture-recognition model for a Prophesee EVK4 event camera from 4.2MB down to...
The Interview Prep Stack I Used as a Senior Software Engineer Targeting Big Tech
Dev.to · Emily Davis 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
The Interview Prep Stack I Used as a Senior Software Engineer Targeting Big Tech
Preparing for senior software engineering interviews at big tech is not just about solving LeetCode...
Principal Components in TypeScript (Part 4)
Dev.to · bitanath 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Principal Components in TypeScript (Part 4)
This is part four of a series Principal Components in TypeScript and focuses on the application of...
Building a Data Drift Detection Framework in Python with Statistical Rigor
Dev.to · Haji Rufai 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Building a Data Drift Detection Framework in Python with Statistical Rigor
Data drift — the silent killer of ML models and data pipelines. Your model worked perfectly in...
Model Routing Cost Checklist: Hosted APIs, Open Models, Or Self-Hosted Inference?
Dev.to · Yash Pritwani 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Model Routing Cost Checklist: Hosted APIs, Open Models, Or Self-Hosted Inference?
Originally published on TechSaaS Cloud Originally published on TechSaaS Cloud Model...
Principal Components in TypeScript (Part 3)
Dev.to · bitanath 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Principal Components in TypeScript (Part 3)
This is part three of a series Principal Components in TypeScript and focuses on the application of...
**Machine Learning: The Future of Intelligent Systems**
Dev.to · Talha Yeasin Antor 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
**Machine Learning: The Future of Intelligent Systems**
Machine learning, a subset of artificial intelligence (AI), has been gaining significant attention in...
🔬 Direction 1 closure on JAMES — when the hypothesis fails but the data turns "7-tier monotonic natural-stop gradient"
Dev.to · Hashevolution 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
🔬 Direction 1 closure on JAMES — when the hypothesis fails but the data turns "7-tier monotonic natural-stop gradient"
G Two weeks ago I shipped core/reasoning/budget.py to test whether per-call dynamic token budgets...
Simon Willison's Blog 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
datasette 1.0a30
Release: datasette 1.0a30 The big new feature in this alpha is a new customizable "Jump to..." menu, described in detail in The extensible "Jump to" menu in Dat
Where Did All the Code Playgrounds Go?
Dev.to · Alonso Madrigal 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Where Did All the Code Playgrounds Go?
I wanted to get better at technical interviews. That's really where this story starts. A...
Why Your PyTorch Training Crawls on a Beefy GPU (And How to Fix It)
Dev.to · Alan West 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Why Your PyTorch Training Crawls on a Beefy GPU (And How to Fix It)
Your GPU sits at 15% utilization and bigger batches don't help? Here's how to diagnose whether you're compute, memory, or overhead bound — and fix it.
Simon Willison's Blog 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
datasette-fixtures 0.1a0
Release: datasette-fixtures 0.1a0 One of the smaller features in Datasette 1.0a30 is this: New documented datasette.fixtures.populate_fixture_database(conn) hel
You Don’t Need Maths to Be a Good Programmer — But That’s Not the Full Truth
Dev.to · Segun 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
You Don’t Need Maths to Be a Good Programmer — But That’s Not the Full Truth
There’s a popular statement in tech: “You don’t need maths to be a good programmer.” It’s often said...
CRACKING CODING INTERVIEW
Dev.to · Seenivasan A 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
CRACKING CODING INTERVIEW
Technical interviews at top companies like Google, Amazon, and Meta are often centered around coding...
114 pages of ML math, and what actually shows up at work
Dev.to · Thousand Miles AI 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
114 pages of ML math, and what actually shows up at work
Sixty-two pages of machine learning math. Fifty-two pages of deep learning math. One hundred and...
I Wanted To Build AI. Instead I Met Linear Algebra
Dev.to · VishnuRv 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I Wanted To Build AI. Instead I Met Linear Algebra
When I first started learning machine learning, I was genuinely confident. In my head ML was...
I Solved 512+ LeetCode Problems, and Here’s What I Learned 🧠
Dev.to · Gregory 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I Solved 512+ LeetCode Problems, and Here’s What I Learned 🧠
Hi everyone, my name is Greg. I've been working in web development since 2020. A few years ago, I...
AutoML Guide
Dev.to · Luis M 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
AutoML Guide
Build powerful machine learning models directly in SQL without writing any Python code.
Why My Baseline Random Forest Model Beat XGBoost: A Deep Dive into the Titanic Survival Prediction Dataset
Dev.to · Gatusso 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Why My Baseline Random Forest Model Beat XGBoost: A Deep Dive into the Titanic Survival Prediction Dataset
A practical look at feature engineering, model optimization, and why simpler models...
How I Built a Late Delivery Risk Predictor for APL Logistics: What a 95% Delay Rate in First Class Shipping Taught Me About Supply Chain ML
Dev.to · Sugnik Mondal 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
How I Built a Late Delivery Risk Predictor for APL Logistics: What a 95% Delay Rate in First Class Shipping Taught Me About Supply Chain ML
Late deliveries are not just an inconvenience. For a global logistics operator like APL Logistics...
5 Things I Wish I'd Known Before Writing a Production MCP Server in TypeScript (2026)
Dev.to · StemSplit 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
5 Things I Wish I'd Known Before Writing a Production MCP Server in TypeScript (2026)
Retries, mutating vs read-only requests, absolute path validation, structured errors, progress notifications — the rough edges of building a real Model Context
Tracking Chaos: Building a Real-Time Flight Anomaly Engine with Django, Celery, and Machine Learning
Dev.to · Debjit Dey 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Tracking Chaos: Building a Real-Time Flight Anomaly Engine with Django, Celery, and Machine Learning
Imagine walking outside on a quiet afternoon. You hear a sharp roar overhead, pull out your phone,...
KV cache eviction improves long‑context performance
Dev.to · Papers Mache 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1mo ago
KV cache eviction improves long‑context performance
A learned, globally‑calibrated KV‑cache eviction policy can shave memory usage and, paradoxically,...
The Pipeline Architect's Worst Nightmare: Batch vs Streaming in Treasure Hunt Engines
Dev.to · ruth mhlanga 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
The Pipeline Architect's Worst Nightmare: Batch vs Streaming in Treasure Hunt Engines
The Problem We Were Actually Solving In our previous setup, we had a batch processing...
Natural-language SQL needs an explain plan before it runs
Dev.to · Mads Hansen 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Natural-language SQL needs an explain plan before it runs
Natural-language SQL should not go straight from prompt to production query. The generated SQL may...
Linear Regression for Beginners: Simple Linear Regression
Dev.to · Stacy Omwoyo 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Linear Regression for Beginners: Simple Linear Regression
Every day, companies try to predict future outcomes: How much revenue they might generate Which...
I Build ML Infrastructure for a Living — Here's Why Hermes Agent Changes the Game for Platform Engineers
Dev.to · Sodiq Jimoh 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I Build ML Infrastructure for a Living — Here's Why Hermes Agent Changes the Game for Platform Engineers
Hermes Agent Challenge Submission: Write About Hermes Agent Challenge Page I've spent the past...
# Introduction to Machine Learning: How We Arrive at Linear Regression
Dev.to · Stacy Omwoyo 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
# Introduction to Machine Learning: How We Arrive at Linear Regression
Before we talk about Linear Regression, we first need to understand the bigger idea it belongs to ...
I Built a Neural Network Engine in C# That Runs in Your Browser - No ONNX Runtime, No JavaScript Bridge, No Native Binaries
Dev.to · Todd Tanner 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
I Built a Neural Network Engine in C# That Runs in Your Browser - No ONNX Runtime, No JavaScript Bridge, No Native Binaries
Eight months ago the creator of ILGPU told me supporting Blazor WebAssembly would be too difficult. Today I'm shipping a six-backend ML library to NuGet with fi
# Multi-Head Latent Attention (MLA)
Dev.to · Sirajuddin Shaik 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
# Multi-Head Latent Attention (MLA)
Compressing KV cache via low-rank projections - the attention mechanism behind DeepSeek-V2/V3 and...
# Multi-Head Latent Attention (MLA)
Dev.to · Sirajuddin Shaik 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
# Multi-Head Latent Attention (MLA)
Compressing KV cache via low-rank projections - the attention mechanism behind DeepSeek-V2/V3 and...
Code Coverage .NET
Dev.to · davinceleecode 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Code Coverage .NET
Code Coverage .NET For .NET projects, the most common manual way is using: coverlet or...
Multi-Head Latent Attention (MLA)
Dev.to · Sirajuddin Shaik 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Multi-Head Latent Attention (MLA)
Compressing KV cache via low-rank projections — the attention mechanism behind DeepSeek-V2/V3 and...
Stop Trusting Your Accuracy Score: A Practical Guide to Evaluating Logistic Regression Models
Dev.to · Gervais Yao Amoah 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Stop Trusting Your Accuracy Score: A Practical Guide to Evaluating Logistic Regression Models
"Accuracy lied to you. Here's the complete toolkit—confusion matrix, precision, recall, F1, ROC/AUC,...
Ghost in the Stack (Part 1): Why uninitialized variables remember old data
Dev.to · Chisom 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Ghost in the Stack (Part 1): Why uninitialized variables remember old data
Have you ever written a C program, run it, and watched it print values you never assigned? At first...
Why I Spent 6 Months Rebuilding Our Event Pipeline to Fix a 400ms Query Latency Problem
Dev.to · ruth mhlanga 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
Why I Spent 6 Months Rebuilding Our Event Pipeline to Fix a 400ms Query Latency Problem
The Problem We Were Actually Solving I was tasked with optimizing the event pipeline for...
How to Actually Become a Programmer: The Hard Part Nobody Wants to Explain
Dev.to · Alex Vakulov 📐 ML Fundamentals ⚡ AI Lesson 1mo ago
How to Actually Become a Programmer: The Hard Part Nobody Wants to Explain
There is a comfortable myth around becoming a programmer. It says you can watch a few courses, copy a...