John Sandall
@johnsandall.bsky.social
CEO & Principal Data Scientist at coefficient.ai
2️⃣ Are they effectively using techniques like cohorting, backtesting to simulate past futures, and aligning eval metrics to downstream company KPIs?
3️⃣ Would it help to workshop it together? Check out coefficient.ai and we can book in a session, this is exactly what we do at Coefficient!
3️⃣ Would it help to workshop it together? Check out coefficient.ai and we can book in a session, this is exactly what we do at Coefficient!
Coefficient
Coefficient is a data consultancy offering data science, engineering, machine learning and other AI-related services as well as bespoke training courses.
coefficient.ai
March 31, 2025 at 11:59 AM
2️⃣ Are they effectively using techniques like cohorting, backtesting to simulate past futures, and aligning eval metrics to downstream company KPIs?
3️⃣ Would it help to workshop it together? Check out coefficient.ai and we can book in a session, this is exactly what we do at Coefficient!
3️⃣ Would it help to workshop it together? Check out coefficient.ai and we can book in a session, this is exactly what we do at Coefficient!
Some questions to ask your data team:
1️⃣ Are they using the right eval metrics as their "north star"? The wrong model evaluation metric can quietly sabotage your ML team's impact. Choosing between MAE, F1, RMSE and others isn't academic, it's business critical.
1️⃣ Are they using the right eval metrics as their "north star"? The wrong model evaluation metric can quietly sabotage your ML team's impact. Choosing between MAE, F1, RMSE and others isn't academic, it's business critical.
Coefficient
Coefficient is a data consultancy offering data science, engineering, machine learning and other AI-related services as well as bespoke training courses.
coefficient.ai
March 31, 2025 at 11:59 AM
Some questions to ask your data team:
1️⃣ Are they using the right eval metrics as their "north star"? The wrong model evaluation metric can quietly sabotage your ML team's impact. Choosing between MAE, F1, RMSE and others isn't academic, it's business critical.
1️⃣ Are they using the right eval metrics as their "north star"? The wrong model evaluation metric can quietly sabotage your ML team's impact. Choosing between MAE, F1, RMSE and others isn't academic, it's business critical.