This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally used. Learners will also gain skills to contrast the practical consequences of different data preparation steps and describe common production issues in applied ML.
Este curso forma parte de Programa especializado: Machine Learning: Algorithms in the Real World
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Programa - Qué aprenderás en este curso
Classification using Decision Trees and k-NN
Functions for Fun and Profit
Regression for Classification: Support Vector Machines
Contrasting Models
Reseñas
- 5 stars76,04 %
- 4 stars18,51 %
- 3 stars3,20 %
- 2 stars0,98 %
- 1 star1,23 %
Principales reseñas sobre MACHINE LEARNING ALGORITHMS: SUPERVISED LEARNING TIP TO TAIL
I found the course to be enough detailed to get clarity on the basic concepts of Supervised learning algorithms. I hope to apply the learning from the course in work!
A good refresher on some commonly found learning algorithms.
Great learning..Talked almost all important issues.
Excellent course. In which I had in-depth knowledge of all algorithms and the way she explained attracts to listen except for her spontaneity and speed in progressing.
Acerca de Programa especializado: Machine Learning: Algorithms in the Real World

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