About this Course
This course dives into the fundamentals of machine studying utilizing an approachable, and well-known programming language, Python.
- IBM AI Engineering Skilled Certificates
- IBM Information Science Skilled Certificates
WHAT YOU WILL LEARN
Give examples of Machine Studying in varied industries.
Define the steps machine studying makes use of to unravel issues.
Present examples of assorted strategies utilized in machine studying.
Describe the Python libraries for Machine Studying.
SKILLS YOU WILL GAIN
- Python Libraries
- Machine Studying
- regression
- Hierarchical Clustering
- Okay-Means Clustering
Syllabus – What you’ll be taught from this course
1 hour to finish
Introduction to Machine Studying
On this module, you’ll study functions of Machine Studying in several fields akin to well being care, banking, telecommunication, and so forth. You’ll get a normal overview of Machine Studying subjects akin to supervised vs unsupervised studying, and the utilization of every algorithm. Additionally, you perceive the benefit of utilizing Python libraries for implementing Machine Studying fashions.
5 hours to finish
Regression
On this module, you’ll get a short intro to regression. You study Linear, Non-linear, Easy and A number of regression, and their functions. You apply all these strategies on two totally different datasets, within the lab half. Additionally, you discover ways to consider your regression mannequin, and calculate its accuracy.
5 hours to finish
Classification
On this module, you’ll study classification method. You observe with totally different classification algorithms, akin to KNN, Choice Timber, Logistic Regression and SVM. Additionally, you study execs and cons of every methodology, and totally different classification accuracy metrics.
4 hours to finish
Clustering
On this module, you’ll study totally different clustering approaches. You discover ways to use clustering for buyer segmentation, grouping similar automobiles, and likewise clustering of climate stations. You perceive 3 foremost varieties of clustering, together with Partitioned-based Clustering, Hierarchical Clustering, and Density-based Clustering.
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