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 (11,633) Articles (5151)Blog Posts (2353)Tutorials (1029)Research Papers (2742)News (358)
Python Celery Task Queues for Video Metadata Processing
Dev.to · ahmet gedik 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Python Celery Task Queues for Video Metadata Processing
Implement background task processing with Python Celery for thumbnail validation, virality scoring,
How to Speed Up Phrase Search with bigram_index
Dev.to · Sergey Nikolaev 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How to Speed Up Phrase Search with bigram_index
TL;DR bigram_index can be used for several purposes, and in this article we focus...
The Connector Graveyard: What Multi-Model Pipeline Code Actually Looks Like.
Dev.to · Chris Widmer 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
The Connector Graveyard: What Multi-Model Pipeline Code Actually Looks Like.
Every ML team building multi-model pipelines has a graveyard. It is not a literal place. It is a...
I Tested My AI Pipeline 6 Times and Found 9 Bugs. The Model Caused Zero of Them.
Dev.to · Ken Imoto 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
I Tested My AI Pipeline 6 Times and Found 9 Bugs. The Model Caused Zero of Them.
Three separate Claude sessions, three cron jobs, one architecture diagram I felt smug about. Six test runs later I had nine bugs. Every single one was in the ha
Production SageMaker Patterns, Multi-Account Deployment, and Event-Driven Architecture for FSx for ONTAP S3 Access Points — Phase 4
Dev.to · Yoshiki Fujiwara(藤原 善基)@AWS Community Builder 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Production SageMaker Patterns, Multi-Account Deployment, and Event-Driven Architecture for FSx for ONTAP S3 Access Points — Phase 4
TL;DR This is Phase 4 of the FSx for ONTAP S3 Access Points serverless patterns...
Why Full-Stack ML Engineers Are More Valuable Than Pure Data Scientists
Dev.to · Joseph Tobi 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Why Full-Stack ML Engineers Are More Valuable Than Pure Data Scientists
There is a conversation happening in every tech company right now. A data scientist presents a model....
How to Serve a PyTorch Model with FastAPI: A Complete Guide
Dev.to · Joseph Tobi 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How to Serve a PyTorch Model with FastAPI: A Complete Guide
How to Serve a PyTorch Model with FastAPI: A Complete Guide Most machine learning tutorials stop at...
DataAccess: Entity Framework
Dev.to · Bruno Freschi 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
DataAccess: Entity Framework
O Entity Framework (EF Core) fecha essa trindade do acesso a dados no .NET. Enquanto o ADO.NET te dá...
How Bayesian Networks Work — Graphs, Probability, and Inference
Dev.to · shangkyu shin 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How Bayesian Networks Work — Graphs, Probability, and Inference
Bayesian Networks can feel confusing because they combine two things at once. Graphs show...
Feature Engineering — Deep Dive + Problem: Palindromic Substrings
Dev.to · pixelbank dev 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Feature Engineering — Deep Dive + Problem: Palindromic Substrings
A daily deep dive into ml topics, coding problems, and platform features from PixelBank. ...
🐍 The "Production-Ready" Miniconda Cheatsheet: From Homebrew to JupyterLab
Dev.to · Hamdi LAADHARI 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
🐍 The "Production-Ready" Miniconda Cheatsheet: From Homebrew to JupyterLab
As I started my journey into AI and Data Science, I quickly realized that managing Python...
Building Mithridatium: Detecting Hidden Backdoors in ML Models
Dev.to · Pelumi Oluwategbe 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building Mithridatium: Detecting Hidden Backdoors in ML Models
Building an open-source ML backdoor detection framework.
When Your AI Pipeline Grows Up: Infrastructure Thinking for Real-Time Inference at Scale
Dev.to · Ken W Alger 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
When Your AI Pipeline Grows Up: Infrastructure Thinking for Real-Time Inference at Scale
There’s a familiar arc in AI development. A team builds a model, wires up a pipeline, and ships it....
The 10 free books I recommend to every engineer learning ML math (and why order matters)
Dev.to · Terezija Semenski 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
The 10 free books I recommend to every engineer learning ML math (and why order matters)
After teaching hundreds of engineers learn machine learning last 5 years, a pattern becomes hard to...
Day 3 — Moving to Multiple Linear Regression
Dev.to · Rehana Hassan Muhumed 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Day 3 — Moving to Multiple Linear Regression
Today I continued my Machine Learning journey and learned about Multiple Linear Regression. After...
Build a UPI Transaction Categorizer in 95 Lines of Python
Dev.to · Archit Mittal 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Build a UPI Transaction Categorizer in 95 Lines of Python
If you use UPI for everything (and at this point, who in India doesn't?), your bank statement is a...
How I built an invoice extraction API that works on any PDF layout
Dev.to · Francesco Ira 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How I built an invoice extraction API that works on any PDF layout
How I built an invoice extraction API that works on any PDF layout I kept running into the...
How much can a Front-end Developer learn about Machine Learning using only JavaScript?
Dev.to · Nomfundo Mtiyane 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How much can a Front-end Developer learn about Machine Learning using only JavaScript?
Robot Playing Piano by Franck V on Unsplash: https://unsplash.com/photos/U3sOwViXhkY Machine Learning...
What Building a 20GB CSV Validator Taught Me About mmap
Dev.to · NARESH-CN2 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
What Building a 20GB CSV Validator Taught Me About mmap
The Problem: The Ingestion BottleneckMost data pipelines struggle with large-scale ingestion because...
The Room Migration Mistake That Crashed Every User's App
Dev.to · SuriDevs 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
The Room Migration Mistake That Crashed Every User's App
I crashed every existing user of my QR scanner app with one bad Room migration — added a label field,...
Avoiding Common Pitfalls in AI-Powered Predictive Analytics Implementation
Dev.to · Edith Heroux 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Avoiding Common Pitfalls in AI-Powered Predictive Analytics Implementation
Common Pitfalls in AI-Powered Predictive Analytics and How to Avoid Them As the e-commerce...
How to Implement AI-Powered Predictive Analytics in Your E-Commerce Strategy
Dev.to · jasperstewart 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
How to Implement AI-Powered Predictive Analytics in Your E-Commerce Strategy
Step-by-Step Guide to Implementing AI-Powered Predictive Analytics Implementing AI-Powered...
55. Multiple Regression: More Features, More Power (And More Ways to Break Things)
Dev.to · Akhilesh 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
55. Multiple Regression: More Features, More Power (And More Ways to Break Things)
In the last post, you predicted house prices using one feature. One number in, one number out. Real...
MCP Explained Simply: How AI Talk to Your Data
Dev.to · Md Shahjalal 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
MCP Explained Simply: How AI Talk to Your Data
Hello friends Today I want to share something I’m currently learning — MCP (Model Context...
TSP - Travelling Salesman Problem
Dev.to · João Godinho 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
TSP - Travelling Salesman Problem
Introduction I will talk about P vs NP, NP-complete, and NP-hard, define heuristics in...
I built a distributed compute grid where your idle laptop runs ML jobs — here's the architecture
Dev.to · Aman Sachan 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
I built a distributed compute grid where your idle laptop runs ML jobs — here's the architecture
The Problem Most personal computers sit idle 90% of the time. Meanwhile, ML training and...
🌿 Plant Disease Detection System
Dev.to · Somnath Das 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
🌿 Plant Disease Detection System
Agriculture is the backbone of many economies, yet plant diseases continue to cause massive crop...
Migrating a Single-Tenant SaaS to Multi-Tenant Workspaces with EF Core Global Query Filters
Dev.to · Nicolas Florez 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Migrating a Single-Tenant SaaS to Multi-Tenant Workspaces with EF Core Global Query Filters
TL;DR We had a single-tenant Angular + .NET 10 SaaS where every row was scoped by UserId....
I Built My Own Hands-on AI Tutorial – Chapter 1: Regression (From Scratch + XGBoost)
Dev.to · zkaria gamal 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
I Built My Own Hands-on AI Tutorial – Chapter 1: Regression (From Scratch + XGBoost)
A few weeks ago, I revisited my old AI/ML projects. As I looked through the code, I felt something...
The real problem with ingesting MongoDB into Delta Lake (and how I built a library to fix it)
Dev.to · Luiz Oliveira 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
The real problem with ingesting MongoDB into Delta Lake (and how I built a library to fix it)
If you've ever built ETL pipelines pulling data from MongoDB into Delta Lake using Spark, you've...
Writing Effective Unit Tests: Best Practices
Dev.to · GeekyAnts Inc 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Writing Effective Unit Tests: Best Practices
Master unit testing in JavaScript with Jest. Learn AAA pattern, mocking, isolation, test coverage,...
53. Overfitting: When Your Model Is Too Good at Being Wrong
Dev.to · Akhilesh 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
53. Overfitting: When Your Model Is Too Good at Being Wrong
Series: How Machines Learn: A Complete Guide from Zero to AI Engineer Phase 6: Machine Learning (The...
From Kubeflow to Real-World ML: Why Data Locality Matters Just as Much as Compute
Dev.to · David Aronchick 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
From Kubeflow to Real-World ML: Why Data Locality Matters Just as Much as Compute
From Kubeflow to Real-World ML: Why Data Locality Matters More Than Compute When my...
Why Your 'AI-Ready' Data Isn't: The Hidden Pipeline Problem Breaking Production AI
Dev.to · David Aronchick 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Why Your 'AI-Ready' Data Isn't: The Hidden Pipeline Problem Breaking Production AI
The names have been changed to protect the innocent. :) A Fortune 500 retailer spent $5 million on...
The Loop Is Only as Good as the Metric
Dev.to · David Aronchick 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
The Loop Is Only as Good as the Metric
On Thursday I wrote about Karpathy's autoresearch, the 630-line training loop that runs 100 ML...
Simon Willison's Blog 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
TRE Python binding — ReDoS robustness demo
Research: TRE Python binding — ReDoS robustness demo If it's good enough for antirez to add to Redis I figured Ville Laurikari's TRE regular expression engine w
Parallel RNNs?
Dev.to · Denis 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Parallel RNNs?
Did you check out the recent ICLR results? I got intrigued by a rather provocative paper from Apple -...
I Built an AI That Predicts Medical Specialties from Clinical Notes (End-to-End Deployment)
Dev.to · Sheikh Sadi Asif 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
I Built an AI That Predicts Medical Specialties from Clinical Notes (End-to-End Deployment)
Hey DEV community 👋 I recently built and deployed a full-stack AI system that predicts medical...
Why AI Projects Break After Deployment
Dev.to · Scott McMahan 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Why AI Projects Break After Deployment
A lot of machine learning models perform well in development but fail once they reach production....
Linear Regression: Code (a) Line
Dev.to · the_undefined_architect 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Linear Regression: Code (a) Line
It's time to write your first ML model and predict house prices. To follow along, go ahead and take a...
AI Commerce Needs MLPerf — and Here's an Early Attempt
Dev.to · Benji Fisher 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
AI Commerce Needs MLPerf — and Here's an Early Attempt
Validating a UCP manifest takes a second. Scoring it for agent-readiness takes another. Neither of...
Dimensionality Reduction in Machine Learning: PCA and t-SNE.
Dev.to · Kelvin 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Dimensionality Reduction in Machine Learning: PCA and t-SNE.
Dimensionality reduction is a fundamental concept in machine learning used to reduce the number of...
I Built an AI That Detects Pneumonia From Chest X-Rays Here's Exactly How I Did It
Dev.to · Sheikh Sadi Asif 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
I Built an AI That Detects Pneumonia From Chest X-Rays Here's Exactly How I Did It
A few weeks ago, I shipped PneumoScan AI a deep learning model that analyzes chest X-ray images and...
Understanding Data Types in Python
Dev.to · Gamya 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Understanding Data Types in Python
Python Basics #2 🐍🔥 In the previous article of this Python Basics series, we learned about...
CloudSync MLBridge: Bridging Google Cloud Datastore and BigQuery with ML-Powered Sync
Dev.to · Raghava Chellu 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
CloudSync MLBridge: Bridging Google Cloud Datastore and BigQuery with ML-Powered Sync
If you've built production systems on Google Cloud, you've likely hit the same wall: your operational...
🏈 TensorCraft Playbook: De CNNs de Sala de Aula a Cloud TPUs com Keras
Dev.to · Ahirton Lopes 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
🏈 TensorCraft Playbook: De CNNs de Sala de Aula a Cloud TPUs com Keras
📖 Capítulo 1: A Formação de Ataque (Arquitetura CNN) Toda estratégia vencedora exige fundamentos...
Day 5/75: Prefix sums in Go - Go DSA
Dev.to · Naveen Karasu 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Day 5/75: Prefix sums in Go - Go DSA
A focused walkthrough of prefix sums in go built around using a stable invariant so prefix sums in go feels like a process instead of a trick.
Building an AI-Powered Prediction Engine for Racing Data: A Developer's Journey
Dev.to · Ali Can 📐 ML Fundamentals ⚡ AI Lesson 2mo ago
Building an AI-Powered Prediction Engine for Racing Data: A Developer's Journey
As developers, we are always looking for interesting datasets to test our machine learning skills....