Essential AI Concept - Category - DataSci Ocean

Essential AI Concept

2026

Claude Code Concepts: Agentic Loop, Tools, Skills, and Permissions 07-24

Dropout Explained: The Simple Secret to Preventing Neural Network Overfitting 07-20

Understanding Backpropagation: How Gradients Are Calculated 07-15

An Introduction to Stochastic Gradient Descent 07-09

Deep Learning Fundamentals: An Introduction to Gradient Descent 06-28

Deep Learning Fundamentals: The MNIST Dataset and the Cost Function 06-20

Machine Learning Basics: The Bias-Variance Tradeoff 06-16

An Improved Perceptron: Understanding the Sigmoid Neuron 06-09

Beyond Text-to-SQL: Implementing OpenAI’s 6-Layer Context Data Agent and the Hidden Challenges 04-25

Harness Engineering: Building Self-Evolving AI Agents with Ralph Loop and MemRL 04-05

Takeaways of vLLM Semantic Router 03-29

Beyond the Context Window: A Deep Dive into Context Engineering for AI Agents 03-22

Beyond Prompt Engineering: The System Engineering of AI Agents — Deconstructing Memory, Tool-Making, and Autonomy in OpenClaw 03-16

2024

The 3 Stages of LLM Training: A Deep Dive into Reinforcement Learning from Human Feedback (RLHF) 02-27

2023

Model Inference: The Final Step in the Machine Learning Workflow 02-05

Machine Learning in 5 Steps: How to Evaluate a Model 02-02

Machine Learning Problem-Solving in 5 Steps: Model Training 01-29

How to Build a Dataset for Machine Learning (in 4 Steps) 01-28

Machine Learning in 5 Steps: How to Define the Problem 01-27