Explain the data science process in detail by using a specific case study of your interest.
Answers
Answer:
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Explanation:Data scientists can appear to be wizards who pull out their crystal balls (MacBook Pros), chant a bunch of mumbo-jumbo (machine learning, random forests, deep networks, Bayesian posteriors) and produce amazingly detailed predictions of what the future will hold. However, as much as we’d like to believe it was, data science is not magic and has a widely accepted definition. The power of data science comes from a deep understanding of statistics and algorithms, programming and hacking, and communication skills (check out our list of the best data science books to dive deeper). More importantly, data science is about applying these three skill sets in a disciplined and systematic manner.
Over the last few years, I’ve not only worked as an individual data scientist in several companies, but also led a team of data scientists as chief data scientist at Pindrop Security, a hot Andreessen-Horowitz funded cybersecurity startup. My team worked on several cutting-edge projects using a wide variety of tools and techniques. Over time, I realized that despite the variation in the details of different projects, the steps that data scientists use to work through a complex business problem remain more or less the same.
Answer:
Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.
Explanation: