How to build a machine learing, model in python

1. How to build a machine learning model in Python

2. Machine Learning for Small Businesses https://www.boardinfinity.com/

3. Real-world examples from startups and SMBs Healthcare: Predicted patient charges → fewer billing errors E-commerce: Segmented customers → personalized pricing SaaS: Tagged support tickets → faster response Retail: Forecasted demand → cut inventory costs ML = Automation + Prediction + Personalization https://www.boardinfinity.com/

4. Tools to build your first model Visualization Tools Deployment Tools Python Libraries NumPy – math & arrays Pandas – clean & organize data Scikit-learn – ready- made ML algorithms Jupyter – Matplotlib – line/bar charts Seaborn – heatmaps, distributions Streamlit – interactive dashboards notebooks for code + notes Docker – run models anywhere MLflow – track & manage experiments https://www.boardinfinity.com/

5. Build Your Model in 8 Steps https://www.boardinfinity.com/

6. Avoid these common mistakes Poor Training Balance → Too little = underfit | Too much = overfit → Always split data: train_test_split() Wrong Data = Weak Results → Use recent, relevant behavioral data — not just demographics. No Ongoing Monitoring → ML models degrade over time → Set monthly checks & retrain with new data https://www.boardinfinity.com/

7. support@boardinfinity.com https://www.boardinfinity.com/