- File Size: 4816 KB
- Print Length: 76 pages
- Simultaneous Device Usage: Unlimited
- Publication Date: August 12, 2016
- Sold by: Amazon Digital Services LLC
- Language: English
- ASIN: B01JBL8YVK
- Text-to-Speech: Enabled
- Word Wise: Not Enabled
- Lending: Enabled
- Amazon Best Sellers Rank: #10,440 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners Kindle Edition
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Top customer reviews
I would recommend it if you are just trying to have a better sense of the principles of Random Forest algorithm. You are not going to become an expert in the subject just by reading it.
The author works hard to bring the book comprehensible to a novice such as me. To some degree he succeeds. I have a better understanding now for some of the tools used by data scientists. He provides insight into how to work with data, set up decision trees, determine the size of random forests, consider GINI and Entropy coefficients and determine the relative importance of features in the data.
The book was a good introduction to some of the complexities of data science. I plan to read more. One takeaway that I have is that my personal math and statistics skills need bolstering. The book is a good start. If, like me, you're interested in the area, I recommend it, but you should be prepared to engage the topic respectfully.
That being said it was super clear and easy to read and the author understood when to explain in theory vs code.
If you want to get your feet wet with decision trees this is not a bad place to start but further reading will be required.
It says things like, "you draw a line through the box so the left side has mostly apples and the right side has mostly bananas." My kid could read this.
It explains, and shows, to the novice, what the topic is all about. I get it. I can't do the math, but I get it.
Most recent customer reviews
The ideas presented are very high level.Read more
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