This is an analysis based on Kaggle survey data, details are at https://www.kaggle.com/c/kaggle-survey-2019.
This is an analysis based on Kaggle survey data, details are at https://www.kaggle.com/c/kaggle-survey-2019. Kaggle is a subsidiary of Google LLC online community of data scientists machine learners. It offers data sets, a no-setup, customizable, Jupyter Notebooks environment, machine learning competitions and access free GPUs and a huge repository of community published data & code.
The survey received 19,717 usable respondents from 171 countries and territories. If a country or territory received less than 50 respondents, they were grouped and named “Other” for anonymity.
The survey was live from October 8th to October 28th 2019.
The median response time for those who participated in the survey was approximately 10 minutes.
An overview of the world wide participation is given in the map below. The first three countries with the highest number of participants are:
All numbers of all countries are given in the interactive table below. To find a specific country, type the name in the search field. Surprising facts:
The word frequency word cloud shows that software engineers and data scientist are heavily involved the field of machine learning
Easy histogram plots of all questions can be created in R as shown at https://www.kaggle.com/paultimothymooney/how-to-explore-the-2019-kaggle-survey-data
The purpose of the survey analysis is to create insight into which
are used in the field of machine learning. Contrary to public opinion machine learning is not mainly focused on neural networks.
The results are presented by graphs relating parameters either vs time or vs other parameters, see below for an example
The amount of graphs and information calls for a different format than a blog, therefore the results can be found at a separate website https://uwesterr.github.io/KaggleMlSurvey2019/
For attribution, please cite this work as
Sterr (2020, Jan. 18). Uwe's Blog: Analysis of 2019 Kaggle ML & DS Survey. Retrieved from http://uwesterr.de/posts/2020-01-18-analysis-of-2019-kaggle-ml-ds-survey/
BibTeX citation
@misc{sterr2020analysis, author = {Sterr, Uwe}, title = {Uwe's Blog: Analysis of 2019 Kaggle ML & DS Survey}, url = {http://uwesterr.de/posts/2020-01-18-analysis-of-2019-kaggle-ml-ds-survey/}, year = {2020} }