每日一练 | Data Scientist & Business Analyst 面试题 148

大数据应用 · 公众号 · 大数据 · 2017-08-02 09:01

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从6月15日起，数据应用学院将与你一起温习数据科学（DS）和商业分析（BA）领域常见的面试问题。希望积极寻求相关领域工作的你每天关注我们的问题并且与我们一起思考，我们将会在第二天给出答案。

Day 48

DS Interview Questions

Give me some tips about how to improve the power of Naive Bayes Model.

BA Interview Questions

R language:

Get 1000 simulations of a paired dice game.

A game immediately stops if you have an initial total (2 dice) of 5,6,7,8,9.

If the first cast does not meet those 5 totals you would continue until you get either 11 or 12.

What is the average number of dice casts per game?

欲知答案如何？请见下期分解！

Day 47 答案揭晓

DS Interview Questions

Give me some examples about the applications of Naive Bayes Algorithms.

Real time Prediction: Naive Bayes is an eager learning classifier and it is sure fast. Thus, it could be used for making predictions in real time.
Multi class Prediction: This algorithm is also well known for multi class prediction feature. Here we can predict the probability of multiple classes of target variable.
Text classification/ Spam Filtering/ Sentiment Analysis: Naive Bayes classifiers mostly used in text classification (due to better result in multi class problems and independence rule) have higher success rate as compared to other algorithms. As a result, it is widely used in Spam filtering (identify spam e-mail) and Sentiment Analysis (in social media analysis, to identify positive and negative customer sentiments)
Recommendation System: Naive Bayes Classifier and Collaborative Filtering together builds a Recommendation System that uses machine learning and data mining techniques to filter unseen information and predict whether a user would like a given resource or not

BA Interview Questions

R language:

You have an urn with balls from 1 to 100.

You want to find out how often you need to draw a ball to get number 55.

This is an experiment with replacement – you put the ball back each time you draw.

Simulate 1000 runs of the experiment to get an accurate estimation of the required draws.

Use seed 23 to make the experiment reproducible. Use loops (for, while) for the solution.

数据应用学院

数据应用学院（Data Application Lab）, 北美第一家培训－项目实习－职业辅导－内推一站式专业数据人才输送机构，提供大数据和数据科学培训和公司项目解决方案，由南加州与硅谷的高级数据科学家与数据工程师联合创办，致力于传播数据行业最新应用和知识、培训及输送优秀大数据人才，以填补人才缺口、充分发挥大数据在商业中的力量。2016年被北美著名科技杂志Tech Beacon评为Top Data Camp。

长期招募

TECHNICAL WRITER/翻译志愿者

职责：

深度讨论数据应用
调研行业发展

要求：

对数据应用极为感兴趣
具备数据分析基础
具有一定BUSINESS INSIGHT
写作能力强

感兴趣的同学发送简历及 writing sample 到 [email protected] ，邮件标题 “申请翻译/Technical Writer”。

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