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NEW QUESTION: 1
Which script block will display Hello World in the browser when the script is run?
A. <script type="text/javascript">
var message = "Hello ";
var message2 = "World";
document.write(message + message2);
</script>
B. <script type="text/javascript">
var message = "Hello ";
var message2 = "World";
document.write("message + message2 ");
</script>
C. <script type="text/javascript">
var message = "Hello ";
var message2 = "World";
document.write(message & message2);
</script>
D. <script type="text/javascript">
var message = Hello ;
var message2 = World ;
document.write(message + message2);
</script>
Answer: A
NEW QUESTION: 2
You need to determine whether the poor quality of Lync calls is related to inadequate network bandwidth. What should you do?
A. Disable Quality of Service (QoS) support on all network switches.
B. Enable Jumbo Frames on all network switches.
C. Calculate the current volume of Lync traffic in Contoso, and then confirm that the volume of Lync traffic does not exceed 25 percent of wide area network (WAN) bandwidth.
D. Calculate the current volume of Lync traffic in Litware, and then confirm that volume of Lync traffic does not exceed 50 percent of wide area network (WAN) bandwidth.
Answer: C
NEW QUESTION: 3
What information do you need to make an HTTP request using the Compute Classic REST API?
A. open port 8080 on the firewall by using the RESTport utility, which is referenced in the welcome email after the subscription
B. a REST endpoint URL of the site or region in which you want to manage Compute Classic resources
C. the TCP/IP address of the instance, which is obtained from Oracle Cloud My Services
D. a private key, which is generated at the time the subscription was activated
Answer: B
NEW QUESTION: 4
次のデータセットを使用して、特定の顧客の収入範囲を予測する必要があります。
機能として使用する必要がある2つのフィールドはどれですか？それぞれの正解は完全な解決策を提示します。
注：正しい選択はそれぞれ1ポイントの価値があります。
A. 収入範囲
B. 姓
C. 年齢
D. 教育レベル
E. 名
Answer: C,D
Explanation:
Explanation
First Name, Last Name, Age and Education Level are features. Income range is a label (what you want to predict). First Name and Last Name are irrelevant in that they have no bearing on income. Age and Education level are the features you should use.