Your First Machine Learning Model with Python
Compare NumPy, pandas, Polars and more, then build live: train and evaluate a churn prediction model.
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Learn this topic with a mentor
Don't want to wait for the webinar? Pick how you'd like help. Nothing is paid now — you see the fee before anything is booked.
- Bring your own work — code, campaign, report or plan
- Mentor matched to this topic
- Time, format and fee confirmed by email first
What this session would cover
Proposed outline — the mentor finalises the agenda once this topic is scheduled.
- 1The real problem: ML feels like maths-only theory
- 2The tool landscape: NumPy, pandas, Polars, scikit-learn, PyTorch, TensorFlow, XGBoost, OpenCV, Transformers — what each is for and where they overlap
- 3How to choose: team size, integrations, where your data lives, and today's pricing and availability (checked live, not from memory)
- 4Live practical task: Train and evaluate a churn prediction model
- 5Build the reusable output together: ML project starter
- 6When you don't need a new tool at all, then live Q&A on your own setup
Who it's for
- • Students and developers who want hands-on practice with real tools
You'd leave with
- ML project starter
- A shortlist of 2–3 options from NumPy, pandas, Polars, scikit-learn and others, with the criteria to pick one
- Hands-on practice: train and evaluate a churn prediction model
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