Question

18．With the coming of big data age，data science is supposed to be starved for，of which the adaption can point a profound change in corporate competitiveness．Companies，both born in the digital era and traditional world are showing off their skills in data science．Therefore，it seems to have been creating a great demand for the experts of this type．
Mr Carlos Guestrin，machine learning professor from University of Washington argues that all software applications will need inbuilt intelligence within five years，making data scientists-people trained to analyze large bodies of information-key workers in this emerging"cognitive"technology economy．There are already critical applications that depend on machine learning，a subfield of data science，led by recommendation programs，fraud detection systems，forecasting tools and applications for predicting customer behavior．
Many companies that are born digital-particularly internet companies that have a great number of real-time customer interactions to handle-are all-in when it comes to data science．Pinterest，for instance，maintains more than 100 machine learning models that could be applied to different classes of problems，and it constantly fields requests from managers eager to use this resource to deal with their business problem．
The factors weighing on many traditional companies will be the high cost of mounting a serious machine-learning operation．Netflix is estimated to spend﹩150m a year on a single application and the total bill is probably four times that once all its uses of the technology are taken into account．
Another problem for many non-technology companies is talent．Of the computer science experts who use Kaggle，only about 1，000 have deep learning skills，compared to 100，000who can apply other machine learning techniques，says Mr Goldbloom．He adds that even some big companies of this type are often reluctant to expand their pay scales to hire the top talent in this field．
The biggest barrier to adapting to the coming era of"smart"applications，however，is likely to be cultural．Some companies，such as General Electric，have been building their own Silicon Valley presence to attract and develop the digital skills they will need．
Despite the obstacles，some may master this difficult transition．But companies that were built，from the beginning，with data science at their center，are likely to represent serious competition．

63．Which one is obstacle for many traditional companies to popularize learning operation？C
A．Technological problem．
B．Expert crisis．
C．High cost．
D．Customer interactions．
64．What can not be inferred from the passage about the machine learning？D
A．Machine learning operations are costly in Netflix．
B．Machine learning plays an important role in existent applications．
C．Machine learning experts are not highly paid in some non-technology companies．
D．Machine learning models are not sufficient to solve business problems in Pinterest．
65．The underlined word in the 3rd paragraph"fields"most probably meansC．
A．a(chǎn)voids  B．createsC．solvesD．classifies
66．Which of the following is the best title for this passage？A
A．Data science：a forefront force in tech business
B．Corporate competition：an obstacle to the transition
C．Machine learning：a key to smart technology
D．Technique experts：a decisive factor of the coming era．

Answer 1

分析 本文屬于說明文閱讀，作者通過這篇文章主要向我們描述了數(shù)據(jù)科學(xué)是科技行業(yè)的前沿力量，許多大型企業(yè)都要變革發(fā)展．

解答 63．C．細(xì)節(jié)理解題．根據(jù)第四段The factors weighing on many traditional companies will be the high cost of mounting a serious machine-learning operation可知高成本是傳統(tǒng)企業(yè)推廣學(xué)習(xí)操作的障礙；故選C．
64．D．細(xì)節(jié)理解題．根據(jù)文章Pinterest，for instance，maintains more than 100 machine learning models that could be applied to different classes of problems，and it constantly fields requests from managers eager to use this resource to deal with their business problem可知管理者認(rèn)為Pinterest的機(jī)器學(xué)習(xí)模型是可以解決現(xiàn)有的商業(yè)問題的；故選D．
65．C．詞義猜測題．根據(jù)文章Pinterest，for instance，maintains more than 100 machine learning models that could be applied to different classes of problems，and it constantly fields requests from managers eager to use this resource to deal with their business problem可知管理者認(rèn)為Pinterest的機(jī)器學(xué)習(xí)模型是可以解決現(xiàn)有的商業(yè)問題的；意為解決；故選C．
66．A．推理判斷題．根據(jù)第一段With the coming of big data age，data science is supposed to be starved for，of which the adaption can point a profound change in corporate competitiveness可知這篇文章最好的題目為數(shù)據(jù)科學(xué)：科技行業(yè)的前沿力量；故選A．

點評 本文是一篇廣告布告類閱讀，題目涉及多道主旨大意題，細(xì)節(jié)理解題，推理判斷題．做題時學(xué)生應(yīng)仔細(xì)閱讀原文，把握文章主要內(nèi)容，聯(lián)系文章上下文內(nèi)容并結(jié)合所給選項含義，從中選出正確答案，一定要做到有理有據(jù)，切忌胡亂猜測．