Choosing the Right Machine Learning Algorithm - learn Data Science

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Choosing the Right Machine Learning Algorithm - learn Data Science
Best Data Science Course
Overview of different machine learning algorithms, their pros & cons, and use cases where different algorithms fit
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
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.,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,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,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