Workshop: Machine Learning in Code


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“Machine Learning in Code - Supervised ML tuning essentials” is a rapid immersion into the world of machine l earning, model customization and adaptation f or different projects. House pricing prediction algorithms as well as other real examples of the use of machine learning will be considered during the workshop.

We will:

- Remind some basics regarding how machine learning works and what it is used for

- Discuss essentials of feature selection and model tuning

- Tune the algorithm f or house pricing prediction problem and see how works great stuff discussed before

For people:
- Students
- Beginner and junior data scientists
- Analysts - Developers
- ML-related project managers
Desirable prerequisites:

- Some basic mathematics knowledge ( number, function, logarithm, multidimensional space)

- Some basic programming skills ( variable, cycle, array, file, algorithm)

Workshop program:

- General introduction in Machine Learning motivation and applications ( 40 minutes)

- Short break

- Essentials of supervised machine l earning feature selection and model tuning ( 40 minutes)
- Short break

- Practical application of concepts described above in kaggle's House Prices " getting started" competition and Q&A ( 2.5 hours)

In the last section we will collectively guess and t est various features and models t o develop basics of ML intuition. The workshop's attendees will l earn in which cases and how t o apply simple ML routines instead of hearing some buzzwords or discussing t oo specific stuff.


+38 099 055-23-92 - Data Science UA