AI Unveiled: Decoding the Machine Learning Lifecycle
research#machine learning📝 Blog|Analyzed: Feb 12, 2026 15:15•
Published: Feb 12, 2026 15:06
•1 min read
•Qiita AIAnalysis
This article offers a clear and concise overview of the machine learning workflow, breaking down the process into easily digestible steps. It highlights the crucial difference between 'Training' and 'Inference', making the complex world of AI more accessible and understandable.
Key Takeaways
- •The machine learning lifecycle consists of six key steps, from data preparation to evaluation.
- •The fundamental difference lies between creating the model (training) and applying the model (inference).
- •Cross-validation is essential for accurately assessing the model's general performance.
Reference / Citation
View Original"The article explains the difference between the 'Training' phase, which builds the ML model, and the 'Inference' phase, which uses the model to make predictions."