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    Automated Machine Learning with Microsoft Azure PDF 下載
    發布于:2024-06-01 10:36:06
    (假如點擊沒反應,多刷新兩次就OK!)

    Automated Machine Learning with Microsoft Azure PDF 下載 圖1

     

     

    資料內容:

    Explaining data science's ROI problem
    Data scientist has been consistently ranked the best job in America by Forbes Magazine 
    from 2016 to 2019, yet the best job in America has not produced the best results for the 
    companies employing them. According to VentureBeat, 87% of data science projects fail 
    to make it into production. This means that most of the work that data scientists perform 
    does not impact their employer in any meaningful way.
    By itself, this is not a problem. If data scientists were cheap and plentiful, companies 
    would see a return on their investment. However, this is simply not the case. According 
    to the 2020 LinkedIn Salary stats, data scientists earn a total compensation of around 
    $111,000 across all career levels in the United States. It's also very easy for them to find 
    jobs. 
    Burtch Works, a United States-based executive recruiting firm, reports that, as of 2018, 
    data scientists stayed at their job for only 2.6 years on average, and 17.6% of all data 
    scientists changed jobs that year. Data scientists are expensive and hard to keep. 
    Likewise, if data scientists worked fast, even though 87% of their projects fail to have 
    an impact, a return on investment (ROI) is still possible. Failing fast means that many 
    projects still make it into production and the department is successful. Failing slow means 
    that the department fails to deliver. 
    Unfortunately, most data science departments fail slow. To understand why, you must 
    first understand what machine learning is, how it differs from traditional software 
    development, and the five steps common to all machine learning projects. 
    Defining machine learning, data science, and AI
    Machine learning is the process of training statistical models to make predictions using 
    data. It is a category within AI. AI is defined as computer programs that perform cognitive 
    tasks such as decision making that would normally be performed by a human. Data 
    science is a career field that combines computer science, machine learning, and other 
    statistical techniques to solve business problems.

     

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