For the following floor plan, is it possible to find a route that begins in one room, passes through each doorway exactly once, and ends in the starting room?

What is the length of the following array? x = np.linspace(-1, 7, 23)

Consider the following code that we used to classify the income of adults in the US.inputs = tf.keras.layers.Dense(units=32, activation=’relu’, input_shape=[len(features.columns)]) hidden = tf.keras.layers.Dense(units=32, activation=’relu’) outputs = tf.keras.layers.Dense(units=2, activation=TO BE FILLED) model = tf.keras.Sequential([inputs, hidden, outputs]) loss = ‘sparse_categorical_crossentropy’ optimizer = tf.keras.optimizers.RMSprop(0.001) model.compile(loss=loss, optimizer=optimizer, metrics=[‘accuracy’])What was the activation function used on the output layer in this deep neural network?

Which of the following is the relationship within sentence 11?

Which of the following is the relationship between sentences six and seven?

Assume we download the stock price of Tesla using the command  startdate = ‘2019-01-01’ enddate = ‘2021-01-01’ tesla = web.get_data_yahoo(“TSLA”, startdate, enddate)tesla Date Open High Low Close Adj Close Volume 2019-01-02 61.220001 63.026001 59.759998 62.023998 62.023998 58293000 2019-01-03 61.400002 61.880001 59.476002 60.071999 60.071999 34826000 2019-01-04 61.200001 63.599998 60.546001 63.537998 63.537998 36970500 2019-01-07 64.344002 67.348000 63.549999 66.991997 66.991997 37756000 2019-01-08 68.391998 68.802002 65.403999 67.070000 67.070000 35042500   Which of the following commands is a valid command to select the “Adj Close” column?

Contrast the code we used in the lecture with the one below that cannot be used in a classification problem.1)inputs = tf.keras.layers.Dense(units=32, activation=’relu’, input_shape=[numwords]) 2)hidden = tf.keras.layers.Dense(units=32, activation=’relu’) 3)hidden2 = tf.keras.layers.Dense(units=32, activation=’relu’) 4)outputs = tf.keras.layers.Dense(units=1, activation=’relu’) 5)model = tf.keras.Sequential([inputs, hidden, hidden2, outputs])6)model.compile(loss=loss, optimizer=optimizer, metrics=[‘accuracy’]) 7) history = model.fit(x_train, y_train, validation_split=0.2, epochs=16, batch_size=512, verbose=0)Which line prevent us from using the code above in a binary classification problem?

Phenol red is a _______________.

Which of the following examples is not an example of a nonlinear function?

Consider a portfolio with the following weights w and the expected return on each risky asset ER below. w = np.array([0.05, 0.03, 0.15, 0.32, 0.09, 0.07, 0.05, 0.13, 0.11]) ER = np.array([0.10, 0.02, 0.05, 0.03, 0.07, 0.055, 0.034, 0.017, 0.026]) Which of the following expressions represents the portfolio expected return in Python?