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NEW QUESTION: 1
Consumers have rights in terms of any information collected about them through your digital marketing campaigns. What legislation are these rights protected under? Choose one of the following:
Exhibit:

A. Data Protection Act
B. Accessibility Act
C. Privacy Act
D. Disability Act
Answer: A
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 2
The above is the display startup information of the AR2200 router. For this information, the error is ().

A. The system file of the next startup of the device can be modified by using the command "startup system software<startup-software-name>.cc".
B. The system file cannot be modified when the device starts next time.
C. The running configuration file is not saved
D. When the device starts using the system file, ar2220-v200r003c00spc200.cc
Answer: B

NEW QUESTION: 3
What is the exemption criteria U/S 10(10) (ii) of the IT Act, 1961 for any gratuity received by a seasonal employee?
A. Exemption limit is least of three:
(i) 15 day's wages based on last drawn salary for every completed year
(ii) Rs. 4,00,000/-,
(iii) Actual gratuity received
B. Exemption limit is least of three:
(i) 15 day's wages based on last drawn salary for every completed year
(ii) Rs. 3,50,000/-,
(iii) Actual gratuity received
C. Exemption limit is least of there:
(i) 7 day's wages (calculated as 26 working days in a month) based on last drawn salary for every number of seasons worked, (ii) Rs. 3,50,000/-, (iii) Actual gratuity received
D. Exemption limit is least of three:
(i) 7 day's wages based on last drawn salary for every number of seasons worked, (ii) Rs. 3,00,000/-, (iii) Actual gratuity received
Answer: C

NEW QUESTION: 4
近くの気象観測所からデータを収集します。次のデータを含むweather_dfという名前のパンダデータフレームがあります。

データは正午と深夜の12時間ごとに収集されます。
自動機械学習を使用して、今後7日間の気温を予測する時系列モデルを作成することを計画しています。トレーニングの最初のラウンドでは、最大50の異なるモデルをトレーニングする必要があります。
Azure Machine Learning SDKを使用して自動機械学習実験を実行し、これらのモデルをトレーニングする必要があります。
自動機械学習の実行を構成する必要があります。
AutoMLConfig定義をどのように完了する必要がありますか？回答するには、回答領域で適切なオプションを選択します。
注：正しい選択はそれぞれ1ポイントの価値があります。

Answer:
Explanation:

Explanation


Box 1: forcasting
Task: The type of task to run. Values can be 'classification', 'regression', or 'forecasting' depending on the type of automated ML problem to solve.
Box 2: temperature
The training data to be used within the experiment. It should contain both training features and a label column (optionally a sample weights column).
Box 3: observation_time
time_column_name: The name of the time column. This parameter is required when forecasting to specify the datetime column in the input data used for building the time series and inferring its frequency. This setting is being deprecated. Please use forecasting_parameters instead.
Box 4: 7
"predicts temperature over the next seven days"
max_horizon: The desired maximum forecast horizon in units of time-series frequency. The default value is 1.
Units are based on the time interval of your training data, e.g., monthly, weekly that the forecaster should predict out. When task type is forecasting, this parameter is required.
Box 5: 50
"For the initial round of training, you want to train a maximum of 50 different models." Iterations: The total number of different algorithm and parameter combinations to test during an automated ML experiment.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.auto