What you’ll learn
- Machine learning concepts
- How to code and access data stored in a cloud environment
- Simple and Multiple Linear Regression
- Logistics Regression
- Decision Tree
- Random Forest
- XG Boost
- Unsupervised Algorithms – Centroid (kNN based) and Hierarchical
- How to go about a ML project
This course covers the concepts of machine learning as well as the application of these concepts using case studies and examples, along with a walk through of the python codes.
The following algorithms are covered in detail:
- Simple and multiple linear regression
- Logistic regression
- Decision tree, Random forest and XG boost
- Unsupervised algorithms – Cluster (kNN based) and Hierarchical.
Who this course is for:
- Professionals wanting to shift to ML roles
- Students
- ML professionals who are looking for a refresher
How to Enroll Machine Learning Using Google Cloud course?
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