Choosing the Right Machine Learning Algorithm
What you'll learn
- 1. Overview of different machine learning algorithms
- 2. Pros and cons of different machine learning algorithms
- 3. Practical use cases of different machine learning algorithms
- 4. Figure out which machine learning algorithms works for a particular business problem
Requirements
- Although there is no background required as such for most of the course, however having a little understanding of statistics and programming fundamentals will be helpful.
- The course examples have source code in Python which are there for developers who want to try out different algorithms and not necessary to understand to complete the course.
Description
This course covers the basics of the following algorithms:
Linear Regression
Logistics Regression
Decision Trees
K-Means
PCA
Support Vector Machines
Random Forest
Apriori
Adaptive Boosting
Naïve Bayes
Neural Networks
For each of these, the course dives into the underlying concept, pros & cons, and the different practical business use cases where each of these algorithms work well. For those interested in getting their hands dirty, there are also sample implementations of the algorithms in Python
Who this course is for:
- This course is targeted at people who are in early stages of their data science career and for managers/executives who want to get an overview of different machine learning algorithms
Instructor
![TechTales Inc.](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 3.5 Instructor Rating
- 12 Reviews
- 151 Students
- 2 Courses
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The trainers at TechTales are expert practitioners who spent years in the industry and bring with them their experience in building courses that are very hands on and, include tips and material that can be used by students in their jobs.