10/31/2022 0 Comments Top software for data analysisPyTorch has also significantly increased its share. Tensorflow remains the dominant platform, and Keras continue to grow as a very popular wrapper on top of Tensorflow. Some of the decline may be due to lack of vendor campaign to vote in KDnuggets Poll, and some may reflect decline in popularity of the platform as is probably the case for IBM.ĭeep Learning Tools The share of users of Deep Learning tools jumped to 49.8% (!!), from 33% of voters in 2018 and 32% in 2017. Table 3: Major Analytics/Data Science Platform with the largest decline in usage Platform Tools that had at least 2% share in 2018 and declined 25% or more in their share in 2019 are in the next table. This trend which also existed in 2018 suggests continuing consolidation of Data Science / Machine Learning platforms. There were 48 tools with 2% or higher share in 2018, and among them 14 (less than one third) have increased share in 2019, while 34 have decreased their share. Table 2: Major Analytics/Data Science/ML Software with the largest increase in usage Software The table below lists the tools were included in KDnuggets Poll in 2018 and have grown 20% or more in share and reached at least 25 voters in 2019. In 2019 we added a number of new entries, and eight of them received at least 25 votes: So, if you are an aspiring Data Scientist, learn not only TensorFlow but also SQL - it will likely be useful for many more years. SQL is steady, with a share above 30% for many years. The shares for Deep Learning platforms Tensorflow and especially Keras have grown each year, reflecting the growing usage of Deep Learning in many applications. Several users commented that RStudio should be included, and we will include it in the next poll. R language share has declined 2 year in a row, but less this year than in the previous year. I note that RapidMiner is not a current advertiser on KDnuggets. RapidMiner kept its share at around 51%, which was a reflection of both a large user base and a successful campaign to motivate its users. Python stayed at the top, with almost the same share (65.8% vs 65.6%) of respondents as in 2018. Here are some observations on 3-year trends for top tools. The average number of tools per respondent was 6.7, very consistent with 7.0 in 2018 and 6.75 in 2017 Poll. Here 201 N % share is % of voters who used this software in year 201 N. Table 1: Top Analytics/Data Science/ML Software in 2019 KDnuggets Poll Software Interestingly, we see the same group of top 11 tools (each with at least 20% share) in 2019 as in 2018. Top Analytics, Data Science, Machine Learning Softwareįig 1: KDnuggets Analytics/Data Science 2019 Software Poll: top tools in 2019, and their share in the 2017, 2018 polls More detailed association analysis and anonymized data will be published later. Here is my initial analysis based on remaining participants, after "lone" voters were removed. We removed about 180 such "lone" votes (2/3 were from one vendor), because even if they represented legitimate users of that tool, their experience was not representative of what Data Scientists do in 2019. The average voter chose 6.1 different tools, so voters with just one choice stood out. The 20th annual KDnuggets Software Poll had over 1,800 participants.
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