These are chat archives for FreeCodeCamp/DataScience

Mar 2018
Eric Leung
Mar 27 2018 01:09

A PeerJ (biomedical science journal) collection on Practical Data Science for Stats.


The "Practical Data Science for Stats" Collection contains preprints focusing on the practical side of data science workflows and statistical analysis. Curated by Jennifer Bryan and Hadley Wickham.

There are many aspects of day-to-day analytical work that are almost absent from the conventional statistics literature and curriculum. And yet these activities account for a considerable share of the time and effort of data analysts and applied statisticians.

The goal of this collection is to increase the visibility and adoption of modern data analytical workflows.

We aim to facilitate the transfer of tools and frameworks

  • between industry and academia
  • between software engineering and Stats/CS
  • across different domains
Ajayi Olabode
Mar 27 2018 07:05
@erictleung very interesting.
Bigyan Karki
Mar 27 2018 16:11
@evaristoc hi there again. sorry to ask this question again but why is this function returning an array?
def least_squared_error(x, y, thetta):
    error_sum = 0
    m, n = x.shape
    for j in range(0, m):
        for i in range(1, n):
            error_sum += (thetta.T[i] * x[i] - y[i]) ** 2
    return (error_sum) / (2 * m)
Mar 27 2018 16:34
@bigyankarki I think because you are using an operator for the outer product, *. I think it should be the dot method.