After I went successfully through DSE 400, which is in detail described here. I followed up with DSE 501 Machine Learning with R. I was really eager to learn Machine Learning since beginning of my Data Science study, so here was an opportunity and I took it.
First at all I need to say, I really enjoyed it, even though I haven't finished it yet. Last thing which is still on my table even though I am working on it really hard is final project, the 6th assignment. You are choosing it by your self and define proposal by your self, so it's up to you, how difficult it would be. But, I am going backwards. Let's start from beginning.
Main literature which you will follow up during this study is book with same name as course Machine Learning with R by Brett Lantz.
"I have been pushed by my curiosity to learn more, to do more, than one assignment in one time. And my plan is to return to it."
Then there is many different sources from Internet, for example Twitter Text Mining example directly from R Data Mining web. And also discussion about for example Forecasting time series data from StackOverlflow forum.
As it was in previous course DSE 400, there are Google docs slides which came up with the new topic every single week, you can find them here:
- Exploratory Analysis and Statistical Inference
- Usage of k-Nearest Neighbours or Naive Bayes algorithm
- Decision Trees and Linear Regression algorithms
- Application Artificial Neuron Networks and Support Vector Machines
- K-means Clustering and Text Mining
- Final Machine Learning project in R
Difference between DSE 400 and DSE 501 is that DSE 501 has only 6 weeks. It took from 30th of March to 10th of May and it's more topic consistent, since it is single topic. But it's obvious. DSE 400 was intro to Data Science, this is one topic from Data Science only.
The advantage of choosing most interesting assignment from more than one topic per week is even better here than it was in DSE 400 and it was almost turn into perfect stage. In some cases I have been pushed by my curiosity to learn more, to do more, than one assignment in one time. And my plan is to return to it.
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