Neural Networks for Beginners: An Easy Textbook for Machine Learning Fundamentals to Guide You Implementing Neural Networks with Python and Deep

**** "Neural Networks for Beginners" by Russel R. Russo attempts to serve as an introductory guide to the complex world of machine learning and neural networks. However, customer feedback highlights significant concerns that detract from its overall efficacy as an educational resource. Reviewers point out that the book feels unfinished, citing missing diagrams and repeated references to examples that are not included. Specifically, Chapter 12 has been described as chaotic and out of place, leaving readers confused rather than enlightened. While the text offers a general overview and background on neural networks, it lacks the specifics one's likely to seek when trying to grasp the practical implementation of these models. Certain phrases, like the unintroduced reference to the "adam" optimizer, can lead to frustration for readers who expect clarity and thoroughness. The enthusiasm for coding examples is met with disappointment, as the single example provided is noted to be convoluted and difficult to follow. Readers seeking a foundational understanding of artificial neural networks and their history might find value in this book, but those looking to develop practical coding skills or a hands-on approach are likely to be disappointed. The sentiments collectively suggest that while this book has potential, it requires critical revisions and updates to make it truly beneficial for beginners in the field. **Pros and Cons:** **