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
Easy and engaging. But would loved it more if some more coding examples were given.
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.
This is an excellent course which goes into some depth on the different ML models and underlying complexity but it avoids getting bogged down into the details too much.
The whole specialization is extremely useful for people starting in ML. Highly recommended!
About the Machine Learning: Algorithms in the Real World Specialization
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