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.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Machine Learning: Algorithms in the Real World
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Über diesen Kurs
Lehrplan - Was Sie in diesem Kurs lernen werden
Classification using Decision Trees and k-NN
Functions for Fun and Profit
Regression for Classification: Support Vector Machines
Contrasting Models
Bewertungen
- 5 stars76,16 %
- 4 stars18,42 %
- 3 stars3,19 %
- 2 stars0,98 %
- 1 star1,22 %
Top-Bewertungen von MACHINE LEARNING ALGORITHMS: SUPERVISED LEARNING TIP TO TAIL
The explanation of the topics are easy to understand due to the dynamics of theory, practical exercises and quizzes.
Excellent course for an overview of different ML algorithms. The course is made from a perspective of giving insights in process and not too many mathematical details.
A good refresher on some commonly found learning algorithms.
although the course felt a little hurried, I found the course and the instructor to be very engaging. I look forward to learning more
Über den Spezialisierung Machine Learning: Algorithms in the Real World

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