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Tag Archives | machine learning

A Majority of Data Scientists Lack Competency in Advanced Machine Learning Areas and Techniques

Data science requires the effective application of skills in a variety of machine learning areas and techniques. A recent survey by Kaggle, however, revealed that a limited number of data professionals possess competency in advanced machine learning skills. About half of data professionals said they were competent in supervised machine learning (49%) and logistic regression […]

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How Data Science Helps Customer Success Leaders Answer 5 Important Questions About Customer Churn

Data science methods and related tools (i.g., predictive analytics, machine learning) can help companies improve their customer success programs by answering 5 important questions about customer churn, including what is the current churn/retention rate (e.g., descriptive analytics), who is at risk for churning (predictive analytics), what actions can prevent churn (i.e., prescriptive analytics) and more. […]

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Machine Learning Engineers and Data Scientists Report Highest Job Satisfaction Among Data Professionals

Results from the Kaggle State of Data Science and Machine Learning survey of data professionals revealed that job satisfaction varies widely across job titles. Data professionals who reported the highest level of job satisfaction were: 1) Machine Learning Engineers, 2) Data Scientists and 3) Predictive Modeler. Data professionals who reported the lowest level of job […]

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Top Machine Learning and Data Science Methods Used at Work

The practice of data science requires the use algorithms and data science methods to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals used data visualization, logistic regression, cross-validation and decision trees more than other data science methods in 2017. Looking ahead to 2018, data professionals […]

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Which Data Science Tools are Used Together?

Analysis of usage of 48 data science tools by over 10,000 data professionals showed that data science tools could be grouped into a smaller set (specifically, 14 tool groupings). That is, some data science tools tend to be used together apart from other data science tools. Implications for vendors and data professionals are discussed. Data […]

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Data Science/Analytics Tools, Technologies and Languages used in 2017

Most Used Data Science Tools and Technologies in 2017 and What to Expect for 2018

The practice of data science requires the use of analytics tools, technologies and languages to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals relied on Python, R and SQL more than other tools in 2017. Looking ahead to 2018, the survey results showed that data […]

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Top BOB Blog Posts for 2017: Data Science, Machine Learning and Customer Analytics Best Practices

The importance of analytics continues to grow in business and beyond. I did my part this year to spread interest in analytics to more people. All of my top blog posts of 2017 (most reads) are all related to analytics, with posts that address data science, artificial intelligence and machine learning. Below are my top […]

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Why You Need to Adopt Data Science and Machine Learning in your Customer Experience/Success Program

A study of 80+ companies showed that analytical leading companies (those who use analytics to gain a competitive advantage), more so than analytical lagging companies, leverage their data differently. Analytical Leaders focus their analytics to improve customer loyalty while Analytical Laggards focus their efforts primarily to reduce enterprise costs. Additionally, Analytical Leaders, compared to Analytical […]

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