Machine Learning (ML) · Intermediate level

Intermediate level · Module 6 of 6 · 17 guided hours

Intermediate Machine Learning Project

Deliver the agent liquidity forecast and segmentation project end to end and present it to a business audience.

Learning objectives

  • Plan an ML project with clear success criteria
  • Build, tune and evaluate the solution rigorously
  • Communicate results, limits and monitoring needs

Topics

  • problem framing and success criteria
  • pipeline and tuning
  • segmentation
  • evaluation and costs
  • report and presentation
  • monitoring plan

Lessons

  1. Lesson 1 Framing the Project

    Define the decision, the success criteria and the data available before building anything.

    project briefsuccess criteriaconstraintsrisks

  2. Lesson 2 Building and Evaluating

    Build the pipeline, tune it, segment agents and evaluate everything against the brief.

    pipelinetuning logtest evaluationsegment-wise performance

  3. Lesson 3 Reporting and Presenting

    Write a business report and present the results, recommendations, limits and monitoring plan.

    executive summaryrecommendationlimitsmonitoring plan

Practical activity

Deliver the level project through three reviewed stages: plan, build and evaluate, report and present.

Expected outcomes

  • A rigorous end-to-end ML project
  • Business communication of ML results

Assessment

The level project assessed against its criteria with a presentation to a 'business manager'.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.