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.
About this Course
- 5 stars76.04%
- 4 stars18.51%
- 3 stars3.20%
- 2 stars0.98%
- 1 star1.23%
TOP REVIEWS FROM MACHINE LEARNING ALGORITHMS: SUPERVISED LEARNING TIP TO TAIL
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.
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.
Learn some valuable insights on scikit-learn capabitlity through the labs
The explanation of the topics are easy to understand due to the dynamics of theory, practical exercises and quizzes.
About the Machine Learning: Algorithms in the Real World Specialization
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