The errata list is a list of errors and their corrections that were found after the product was released.
The following errata were submitted by our customers and have not yet been approved or disproved by the author or editor. They solely represent the opinion of the customer.
Color Key: Serious technical mistake Minor technical mistake Language or formatting error Typo Question Note Update
| Version |
Location |
Description |
Submitted by |
Date submitted |
| PDF |
Page 26
2nd paragraph |
The book reads
"This brings the discussion to the central limit theorem, which states that random samples drawn from a population will approach a normal distribution (a probability distribution that is symmetric and bell shaped) as the sample gets larger"
However, the central limit theorem is actually that the sample mean of population converges to a normal distribution. The sample itself will not necessarily reflect a normal distribution.
|
Anonymous |
Mar 04, 2024 |
| PDF |
Page 233 page. Chapter 8. Recurrent Neural Networks
5th paragraph |
The book reads
The following code block shows how to build the RNN architecture in keras:
# Designing the architecture of the model
model = Sequential()
# First hidden layer
model.add(Dense(num_neurons_in_hidden_layers, input_dim = num_lags,
activation = 'relu'))
But, the code block should be like followings
# Create the RNN model
model = Sequential()
# First RNN layer
model.add(SimpleRNN(units = num_neurons_in_hidden_layers, input_shape = (num_lags, 1)))
|
Anonymous |
Jun 01, 2024 |