11/30/2023 0 Comments Anaconda vs python languafes![]() ![]() Just 10% of respondents said their organization had implemented a solution to ensure fairness and mitigate bias, but Anaconda found 30% were planning to implement a step in the next year.Įxplainability and interpretability of ML models was another large gap. Other top concerns included job losses from automation (19%), advanced information warfare (15%), and lack of diversity and inclusion in the profession (10%). Microsoft president Brad Smith recently called for the government to regulate facial recognition due to racial bias. Both of these issues have been highlighted by the adoption of AI and facial recognition in public surveillance systems. The top problem that most data science folks felt needed to be tackled in artificial intelligence and machine learning was "social impacts from bias in data and models" (31%), followed by "impacts to individual privacy". ![]() ![]() ![]() Other commonly cited skills in short supply were deep learning (27%), communication skills (22%), data visualization (22%), machine learning (21%), Python (20%), and probability and statistics (19%). The top missing skill was in "big data management" at 38%, while 26% said their organization was lacking advanced mathematics, and a quarter cited "business knowledge" as lacking. Just over half (52%) said decision-makers were "mostly data literate".Īnaconda also asked respondents to nominate all the skills they believe their organization were currently lacking. Only 36% described their organization's decision-makers as "very data literate" and actually understood data visualization and models. Still, some 39% said reported that "many" of their business decisions rely on data science, while 35% said only some business decisions were based on insights from their team.Ī quarter of respondents said they lacked the resources for effective analysis, while another quarter said decision-makers at their organization struggle with data literacy, and 11% said they or their team couldn't demonstrate a business impact. It's not clear what impact the pandemic has had on investments in data science tools and technology. Over a third (37%) of 4,299 data science professionals, students and academics who responded to Anaconda's online survey this April to May said their organizations decreased investments in data science, while 26% increased their investment and 24% said investments were flat. It was followed by SQL, R, JavaScript, HTML/CSS, Java, Bash/Shell, C/C++, C Given Anaconda's audience, it's not surprising Python was by far the most popular language used. An impressive 88% of students said they were being taught Python in preparation to enter the data science/machine learning field. Most respondents (63%) said they used Python frequently or always while 71% of educators said they're teaching machine learning and data science with Python, which has become popular because of its ease of use and easy learning curve. But while Python adoption is booming, the fields that are driving it - data science and machine learning - are still in their infancy. Python could soon be the most popular programming language, battling it out for top spot with JavaScript, Java and C, depending on which language ranking you look at. Here's a look at the courses you'll need to learn these programming languages. Where to learn the most popular programming languages ![]()
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