Applied · real AI/ML network optimization · in detail

Six case files. The whole loop, at work.

The course gave you the theory and the lab let you drive it. These are the fully-worked case studies — each with the exact data sources, the model and why that model, the method and guardrails, the honest before/after numbers, the catch that nearly broke it, and the transferable lesson. This is what AI/ML optimization actually looks like when it ships.

On the numbers: these are engineering-representative case files built on the real Ericsson 23.Q2.5 counters and formulas, and on publicly-reported industry result ranges (for example, RAN energy savings of 15–25% are widely published). They are detailed teaching cases — the methodology and the counter mechanics are exact; the specific figures are realistic illustrations, not a single confidential operator engagement.

Ten more, in brief

The catalogue is larger than six. Here are ten further optimization use cases running in real networks, each with its technique, its data, and its typical payoff — the same loop, different repair shop.