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Articles tagged with #python3
Overview We'll see the from scratch aspect of the book play out as we implement several building block functions to help us work towards defining the *Euclidean Distance in code: note: This is chapter 4, Linear Algebra, of Data Science from Scratch...
Chapter 3 of Data Science from Scratch introduces us to visualizing data using matplotlib. This is widely used in the Python ecosystem, although my sense is that people are just as happy, if not more, to use other libraries like seaborn, Altair and b...
In the previous post, we began examining a toy data set see what kind of Python concepts from the crash course we'd see in action. What stands out is the use of collections and comprehension. We'll see this trend continue as data is given to us in t...
This is a continuation of the Data Science from Scratch series. The book opens with a narrative motivating example where you, dear reader, are newly hired to lead data science at DataSciencester, a social network exclusively for data scientists. Jo...
We're nearing the end of our python crash course and will get to the fun stuff for the rest of Data Science from Scratch (by Joel Grus). In this post, we'll briefly acquaint ourselves with pseudo-randomness and regular expressions. The random module...
Iterables and Generators A key concept that is introduced when discussing the creation of "generators" is using for and in to iterate over generators (like lists), but lazily on demand. This is formally called lazy evaluation or 'call-by-need' which ...
