I think there are some mistakes in the book, despite that I don't regret buying this book on one of the Packt price campaigns.
On page 143 first ARMA(1,1) is recommended by AIC and a few lines later it's ARMA(1,0).
Then a plot is shown with the following text 'The preceding plot shows a good fitting of the ARMA(1,0) model to predict stock closing
prices:'. What makes it a good fit ? With 1000 datapoints it's hard to evaluate the predictions on the plot.
When looking at fewer points is seems as the prediction is just a delay of the close price. I have generated a sub plot and added delayed prices, they are almost identical with the predicted prices so unless I have made a mistake the fitting seems pretty poor.

Running the examples also have some trouble.
The file WDIData.csv can't be found on github
You must create directories as plots/ch1
In chapter 5 loading the best generated neural network model will generate errors as that filename is hardcoded and the generated filenames is not a deterministic process.

I already have some experience with Practical Time Series Analysis. I purchased this book to help me stay update with date with new techniques. It does that well.

Awesome deal on quite a few quality textbooks and lectures! Well worth the money, contains quality literature that's very helpful and easy to read.

Not as in-depth as a primary source, but good for a refresher & the python examples (via jupyter notebook) are a nice framework to experiment with.