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The post 22 Widely Used Data Science and MachineLearning Tools in 2020 appeared first on Analytics Vidhya. Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20.
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The year 2019 will be remembered in the software world as the year when containerization, cloud native architectures, and MachineLearning broke out into the mainstream. As we approach the end of the decade, it’s time to look forward to the year 2020 and make some predictions about where these.
Introduction MachineLearning is the trending digital technology in today’s world, The post Bar Chart Race of World Population by 2020 in Python appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon.
This book is thought for beginners in MachineLearning, that are looking for a practical approach to learning by building projects and studying the different MachineLearning algorithms within a specific context.
Introduction Source: App Inventiv Like other industries, 2020 (the COVID-19 pandemic) was a rough patch for the insurance industry. But even then, the phase proved to be a turning point that reinforced the importance of technology, especially MachineLearning and Artificial Intelligence.
The American Mathematical Society (AMS) recently published in its Notices monthly journal a long list of all the doctoral degrees conferred from July 1, 2019 to June 30, 2020 for mathematics and statistics. The degrees come from 242 departments in 186 universities in the U.S. I enjoy keeping a pulse on the research realm for […]
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I train a series of MachineLearning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of MachineLearning models in order to draw the decision boundaries from which the models make predictions in a 2D space, which is useful for illustrative purposes and understanding on how different (..)
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Overview Here is a list of Top 15 Datasets for 2020 that we feel every data scientist should practice on The article contains 5. The post Top 15 Open-Source Datasets of 2020 that every Data Scientist Should add to their Portfolio! appeared first on Analytics Vidhya.
In this use case, available to the public on GitHub, we’ll see how a data scientist, project manager, and business lead at a retail grocer can leverage automated machinelearning and Azure MachineLearning service to reduce product overstock.
We have compiled a list of some of the best (and free) machinelearning books that will prove helpful for everyone aspiring to build a career in the field.
This is a short introduction to Made With ML, a useful resource for machinelearning engineers looking to get ideas for projects to build, and for those looking to share innovative portfolio projects once built.
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As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.
After spending a lot of time thinking about the paths that software companies take toward ML maturity, this framework was created to follow as you adopt ML and then mature as an organization.
When machinelearning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction.
Overview Check out our pick of the 30 most challenging open-source data science projects you should try in 2020 We cover a broad range. The post 30 Challenging Open Source Data Science Projects to Ace in 2020 appeared first on Analytics Vidhya.
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Here we identify the causal effect of video gaming on mental well-being in Japan (2020–2022) using game console lotteries as a natural experiment. This study uses a natural experiment with game console lotteries to identify the causal effect of video gaming on mental well-being in Japan (2020–2022). standard deviations.
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