Foundations

ML Fundamentals

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

11,139
lessons
Skills in this topic
View full skill map →
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 551 reads from curated sources

Traditional Machine Learning in Practice: Learning Paradigms, Algorithm Families, and Evaluation Perspectives
Dev.to · shangkyu shin 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Traditional Machine Learning in Practice: Learning Paradigms, Algorithm Families, and Evaluation Perspectives
Traditional machine learning is more than just algorithms. This guide explains how learning...
I built a free LeetCode visualizer. Here's what I learned making 207 problems animate line by line.
Dev.to · Rajan shukla 📐 ML Fundamentals ⚡ AI Lesson 1w ago
I built a free LeetCode visualizer. Here's what I learned making 207 problems animate line by line.
I spent months grinding LeetCode. I could read solutions. I could even explain them out loud. But the...
Tavsiye Iste Uygulamaları - Detaylı Teknik Analiz Rehberi 2026
Dev.to · FORUM WEB 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Tavsiye Iste Uygulamaları - Detaylı Teknik Analiz Rehberi 2026
Tavsiye İste Uygulamaları: Tarihçe ve Gelişim Tavsiye iste uygulamaları, kullanıcıların ihtiyaç ve...
Your Pipeline Is 28.6h Behind: Catching Machine Learning Sentiment Leads with Pulsebit
Dev.to · Pulsebit News Sentiment API 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Your Pipeline Is 28.6h Behind: Catching Machine Learning Sentiment Leads with Pulsebit
Your pipeline has just missed a crucial 24h momentum spike of -0.175 in the sentiment around machine...
Improving Variational Auto-Encoders using Householder Flow
Dev.to · Paperium 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Improving Variational Auto-Encoders using Householder Flow
Neural Network Learning Systems and Deep Learning: From Perceptrons to Representation Learning
Dev.to · shangkyu shin 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Neural Network Learning Systems and Deep Learning: From Perceptrons to Representation Learning
Deep learning did not appear out of nowhere. It grew from a simple question: can a machine learn...
Dev.to AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Weights & Biases — Deep Dive
Daily deep dive into Weights & Biases — covering W&B, ML experiment tracking, Model registry, Prompts, Weave. Latest News & Announcements CoreWeave
Dev.to AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
8 Things to Check Before You Hire MERN Stack Developers
Projects get over-budgeted, late and code that requires rewriting in a year is developed with a portfolio examination and a bid evaluation. The data that in fac
Dev.to AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Word Embeddings — Deep Dive + Problem: Information Gain
A daily deep dive into ml topics, coding problems, and platform features from PixelBank . Topic Deep Dive: Word Embeddings From the NLP Fundamentals chapter Int
AWS Machine Learning 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Reinforcement fine-tuning on Amazon Bedrock: Best practices
In this post, we explore where RFT is most effective, using the GSM8K mathematical reasoning dataset as a concrete example. We then walk through best practices
5 Useful Python Scripts to Automate Boring Excel Tasks
KDnuggets 📐 ML Fundamentals ⚡ AI Lesson 1w ago
5 Useful Python Scripts to Automate Boring Excel Tasks
Merging spreadsheets, cleaning exports, and splitting reports are necessary-but-boring tasks. These Python scripts handle the repetitive parts so you can focus
Building ML in the Dark: A Survival Guide for the Solo Practitioner
Towards AI 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Building ML in the Dark: A Survival Guide for the Solo Practitioner
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Boitumelo on Unsplash No GPU cluster. No data team. No ML platform. Here’s what actually shi
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
EAGLE: Edge-Aware Graph Learning for Proactive Delivery Delay Prediction in Smart Logistics Networks
arXiv:2604.05254v1 Announce Type: new Abstract: Modern logistics networks generate rich operational data streams at every warehouse node and transportation lane
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
TFRBench: A Reasoning Benchmark for Evaluating Forecasting Systems
arXiv:2604.05364v1 Announce Type: new Abstract: We introduce TFRBench, the first benchmark designed to evaluate the reasoning capabilities of forecasting system
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression
arXiv:2604.04988v1 Announce Type: cross Abstract: Modern deployment often requires trading accuracy for efficiency under tight CPU and memory constraints, yet c
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
PRIME: Prototype-Driven Multimodal Pretraining for Cancer Prognosis with Missing Modalities
arXiv:2604.04999v1 Announce Type: cross Abstract: Multimodal self-supervised pretraining offers a promising route to cancer prognosis by integrating histopathol
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
Learning Stable Predictors from Weak Supervision under Distribution Shift
arXiv:2604.05002v1 Announce Type: cross Abstract: Learning from weak or proxy supervision is common when ground-truth labels are unavailable, yet robustness und
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
YMIR: A new Benchmark Dataset and Model for Arabic Yemeni Music Genre Classification Using Convolutional Neural Networks
arXiv:2604.05011v1 Announce Type: cross Abstract: Automatic music genre classification is a major task in music information retrieval; however, most current ben
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
PCA-Driven Adaptive Sensor Triage for Edge AI Inference
arXiv:2604.05045v1 Announce Type: cross Abstract: Multi-channel sensor networks in industrial IoT often exceed available bandwidth. We propose PCA-Triage, a str
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series
arXiv:2604.05064v1 Announce Type: cross Abstract: Synthetic data is essential for training foundation models for time series (FMTS), but most generators assume
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
CRAB: Codebook Rebalancing for Bias Mitigation in Generative Recommendation
arXiv:2604.05113v1 Announce Type: cross Abstract: Generative recommendation (GeneRec) has introduced a new paradigm that represents items as discrete semantic t
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
What Makes a Good Response? An Empirical Analysis of Quality in Qualitative Interviews
arXiv:2604.05163v1 Announce Type: cross Abstract: Qualitative interviews provide essential insights into human experiences when they elicit high-quality respons
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
Modality-Aware and Anatomical Vector-Quantized Autoencoding for Multimodal Brain MRI
arXiv:2604.05171v1 Announce Type: cross Abstract: Learning a robust Variational Autoencoder (VAE) is a fundamental step for many deep learning applications in m
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper 1w ago
Curvature-Aware Optimization for High-Accuracy Physics-Informed Neural Networks
arXiv:2604.05230v1 Announce Type: cross Abstract: Efficient and robust optimization is essential for neural networks, enabling scientific machine learning model
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting
arXiv:2501.14183v3 Announce Type: replace-cross Abstract: Variate tokenization, which independently embeds each variate as separate tokens, has achieved remarka
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm
arXiv:2505.16932v4 Announce Type: replace-cross Abstract: Computing the polar decomposition and the related matrix sign function has been a well-studied problem
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
StateX: Enhancing RNN Recall via Post-training State Expansion
arXiv:2509.22630v2 Announce Type: replace-cross Abstract: Recurrent neural networks (RNNs), such as linear attention and state-space models, have gained popular
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
Eigen-Value: Efficient Domain-Robust Data Valuation via Eigenvalue-Based Approach
arXiv:2510.23409v3 Announce Type: replace-cross Abstract: Data valuation has become central in the era of data-centric AI. It drives efficient training pipeline
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
ReaMIL: Reasoning- and Evidence-Aware Multiple Instance Learning for Whole-Slide Histopathology
arXiv:2601.10073v2 Announce Type: replace-cross Abstract: We introduce ReaMIL (Reasoning- and Evidence-Aware MIL), a multiple instance learning approach for who
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 1w ago
Incident-Guided Spatiotemporal Traffic Forecasting
arXiv:2602.02528v2 Announce Type: replace-cross Abstract: Recent years have witnessed the rapid development of deep-learning-based, graph-neural-network-based f
Supabase vs Firebase: Which Backend Is Right for Your Next App?
KDnuggets 📐 ML Fundamentals ⚡ AI Lesson 1w ago
Supabase vs Firebase: Which Backend Is Right for Your Next App?
Compare SQL and NoSQL backend services. Find out which BaaS is right for your next app in this neutral guide.
InfoQ AI/ML 📐 ML Fundamentals 1w ago
Article: Bloom Filters: Theory, Engineering Trade‑offs, and Implementation in Go
This article walks you through the Go implementation of Bloom filters to optimize the performance of a recommender. It cover the architectural view, Bloom filte
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper 2w ago
On the "Causality" Step in Policy Gradient Derivations: A Pedagogical Reconciliation of Full Return and Reward-to-Go
arXiv:2604.04686v1 Announce Type: new Abstract: In introductory presentations of policy gradients, one often derives the REINFORCE estimator using the full traj
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Fine-tuning DeepSeek-OCR-2 for Molecular Structure Recognition
arXiv:2604.03476v1 Announce Type: cross Abstract: Optical Chemical Structure Recognition (OCSR) is critical for converting 2D molecular diagrams from printed li
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
RDEx-CMOP: Feasibility-Aware Indicator-Guided Differential Evolution for Fixed-Budget Constrained Multiobjective Optimization
arXiv:2604.03708v1 Announce Type: cross Abstract: Constrained multiobjective optimisation requires fast feasibility attainment together with stable convergence
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
An Improved Last-Iterate Convergence Rate for Anchored Gradient Descent Ascent
arXiv:2604.03782v1 Announce Type: cross Abstract: We analyze the last-iterate convergence of the Anchored Gradient Descent Ascent algorithm for smooth convex-co
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Supervised Dimensionality Reduction Revisited: Why LDA on Frozen CNN Features Deserves a Second Look
arXiv:2604.03928v1 Announce Type: cross Abstract: Effective ride-hailing dispatch requires anticipating demand patterns that vary substantially across time-of-d
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Parent Selection Mechanisms in Elitist Crossover-Based Algorithms
arXiv:2604.04083v1 Announce Type: cross Abstract: Parent selection methods are widely used in evolutionary computation to accelerate the optimization process, y
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization
arXiv:2604.04090v1 Announce Type: cross Abstract: Stochastic bilevel optimization (SBO) has been integrated into many machine learning paradigms recently, inclu
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Learning Robust Visual Features in Computed Tomography Enables Efficient Transfer Learning for Clinical Tasks
arXiv:2604.04133v1 Announce Type: cross Abstract: There is substantial interest in developing artificial intelligence systems to support radiologists across tas
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Incomplete Multi-View Multi-Label Classification via Shared Codebook and Fused-Teacher Self-Distillation
arXiv:2604.04170v1 Announce Type: cross Abstract: Although multi-view multi-label learning has been extensively studied, research on the dual-missing scenario,
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Good Rankings, Wrong Probabilities: A Calibration Audit of Multimodal Cancer Survival Models
arXiv:2604.04239v1 Announce Type: cross Abstract: Multimodal deep learning models that fuse whole-slide histopathology images with genomic data have achieved st
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
A Persistent Homology Design Space for 3D Point Cloud Deep Learning
arXiv:2604.04299v1 Announce Type: cross Abstract: Persistent Homology (PH) offers stable, multi-scale descriptors of intrinsic shape structure by capturing conn
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Boosted Distributional Reinforcement Learning: Analysis and Healthcare Applications
arXiv:2604.04334v1 Announce Type: cross Abstract: Researchers and practitioners are increasingly considering reinforcement learning to optimize decisions in com
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Integer-Only Operations on Extreme Learning Machine Test Time Classification
arXiv:2604.04363v1 Announce Type: cross Abstract: We present a theoretical analysis and empirical evaluations of a novel set of techniques for computational cos
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Context is All You Need
arXiv:2604.04364v1 Announce Type: cross Abstract: Artificial Neural Networks (ANNs) are increasingly deployed across diverse real-world settings, where they mus
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Reproducibility study on how to find Spurious Correlations, Shortcut Learning, Clever Hans or Group-Distributional non-robustness and how to fix them
arXiv:2604.04518v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) are increasingly utilized in high-stakes domains like medical diagnostics and auto
ArXiv cs.AI 📐 ML Fundamentals 📄 Paper ⚡ AI Lesson 2w ago
Cardinality Estimation for High Dimensional Similarity Queries with Adaptive Bucket Probing
arXiv:2604.04603v1 Announce Type: cross Abstract: In this work, we address the problem of cardinality estimation for similarity search in high-dimensional space