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What Top Firms Ask: 100+ Data Science Interview Questions
By Prasad Pore Editor, KDnuggets on March 22, 2017 in Algorithms, Data Science, Google, Hadoop, Interview Questions, Machine Learning, Microsoft, Statistics, UberCheck this out: A topic wise collection of 100+ data science interview questions from top companies.
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Analytics 101: Comparing KPIs
Different business units in the organisation have different behaviours (e.g. turnover rate) and they can’t be compared with each other. So, how can we tell whether the changes in their behaviour are reasons for concern?
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Proxy Indicators: beware of spurious claims
Beware of online and market research studies which can lead to false or spurious claims. We examine several notable examples including Google Street View and Argentina inflation.
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Gartner Data Science Platforms – A Deeper Look
Thomas Dinsmore critical examination of Gartner 2017 MQ of Data Science Platforms, including vendors who out, in, have big changes, Hadoop and Spark integration, open source software, and what Data Scientists actually use.
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The Top 5 KPIs to Consider When Measuring Your Campaign
When it comes to measuring marketing campaign performance or analysing customers in any business, below top 5 Key Performance Indicators (KPIs) needs to be used to strategically drive the business.
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Machine Learning-driven Firewall
Cyber Security is always a hot topic in IT industry and machine learning is making security systems more stronger. Here, a particular use case of machine learning in cyber security is explained in detail.
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The Origins of Big Data
Big Data has truly come of age in 2013 when OED introduced the term “Big Data” for the first time. But when was the term Big Data first used and Why? Here are the results of our investigation.
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Apache Arrow and Apache Parquet: Why We Needed Different Projects for Columnar Data, On Disk and In-Memory
Apache Parquet and Apache Arrow both focus on improving performance and efficiency of data analytics. These two projects optimize performance for on disk and in-memory processing
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Career Advice for Analytics & Data Science Professionals
In our experience working with many quantitative professionals over the years, the two main areas that contribute to long-term career growth are networking and continuous learning. Here is specific advice on how to do this and tips for Continuous Learning.
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 So What is Big Data?
We examine what experts say about Big Data – is it like teenage sex? Is it more than just a large and complex collection of data? And how many Vs are there?
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So What is Big Data?