beginner

Molecular Docking Without the Jargon: A Key, a Lock, and Both of Them Wobble

What a docking score really is, why the pose matters more than the number, six ways docking lies to you, and where 2026 co-folding models fit.

Machine Learning for Biology06

Peptides 101: The Tiny Molecular Sentences Your Body Writes

What a peptide actually is, why order and side chains carry the information, and why 13 residues is a different modelling problem from 300.

Machine Learning for Biology01

What Is an Agent Harness? The Part Everyone Skips

The five parts of an agent harness: capability surface, meaning, policy, approval and audit. Only two of them are about power.

Agent Harness01

Green Padlock, Zero Headache: Let’s Encrypt SSL for Self-Hosted Dify

Let's Encrypt certificates on a self-hosted Dify behind Nginx: the ACME flow, the nginx reload everyone forgets, and how to test without burning rate limits.

Retrieval Metrics Demystified: From BM25 Baselines to EM@5 & Answer F1

What BM25, Recall@k, answer-in-context rate and token F1 actually measure, which number to fix first, and how to compute them without fooling yourself.

Retrieval and RAG01

Brains Behind the Bots: Classical Planning from Ground Up

PDDL, heuristics that sometimes do nothing, HTN, temporal and multi-agent planning, with real planner numbers on Towers of Hanoi.

AI Foundations10

Classical Planning 101: From STRIPS Blocks to Graphplan Magic

How STRIPS turns a to-do list into an algorithm: factored states, progression and regression, delete relaxation, planning graphs, and modern planners.

AI Foundations09

First-Order Logic Made Friendly: From ‘Socrates Is Mortal’ to Automatic Proofs

Quantifiers, unification, forward and backward chaining, and resolution, from Socrates to a solver that finds the proof for you.

AI Foundations08

Logical Agents 101: Slaying the Wumpus with Pure Reason

Knowledge bases, entailment, resolution and SAT solving, learned by staying alive in the Wumpus World, with runnable PySAT code.

AI Foundations07

Constraint Satisfaction 101: From Sudoku Logic to Map-Coloring Zen

Arc consistency, backtracking with MRV and min-conflicts, explained through Sudoku and map colouring, plus what you would actually use today.

AI Foundations06

Adversarial Search 101: From Minimax to AlphaZero, How AI Plans When an Opponent Fights Back

Minimax, alpha-beta pruning, expectiminimax and MCTS: how a program plans when something is planning against it, and what neural evaluation changed.

AI Foundations05

Beyond Classical Search: Hill-Climbers, Hidden Worlds & Agents That Learn on the Fly

Hill climbing, simulated annealing, belief states and online search: what to do when A* is the wrong tool, the world hides half of itself, or there is no map yet.

AI Foundations04

Intelligent Agents & Search: A Baby-Steps Tour from ‘What is Rational?’ to ‘How do we find the goal?’

What an agent actually is, how to turn a problem into a search problem, and why changing one line of priority code turns breadth-first search into A*.

AI Foundations03

Machine Learning 101: PyTorch, TensorFlow & Decision Trees

What a deep-learning framework actually does for you, how a decision tree picks its questions, and which of the three to reach for on real data.

AI Foundations02

Math for AI Made Simple: The Linear-Algebra Lego Set Behind Every Model

Scalars, vectors, matrices and tensors, the five operations every neural network is made of, and the shape rules that cause most of the bugs.

AI Foundations01

From Chaos to Focus: Understanding Transformers & Attention

Attention and the transformer block from first principles, plus what changed by 2026: pre-norm, RMSNorm, RoPE, grouped-query attention and the KV cache.