Python for Programmers: with Big Data and Artificial Intelligence Case Studies

Coming from a Java background and trying to get into ML, this book is excellent in readability and content. It goes through the relevant Python structure, syntax, and libraries, but it assumes knowledge of object-oriented programming so it introduces these topics quickly. This is not a book for someone with no experience. It took me about 2 weeks to work through the entire book (outside my job), including typing in all code (muscle memory!). In the end, I feel confident enough to read Python code and write Python scripts to tie together library functions. With respect to data science and big data, each chapter (1-10) has a small section that is devoted to the topic and the final 6 chapters (11-16) have worked examples using scikit-learn, Keras/TensorFlow, and others. I can hardly imagine how this book could be improved upon. Recommended!

This book will build a strong programmer, it explains almost everything there is to the language then get into artificial intelligence, natural language processing, and bots, but it requires dedication to follow a chapter at a time. in order to get everything at the back of your palms, it will take a sitting for a chapter.

In the past I have learned from other Deital Devloper Books, so I purchased this one.I am new to learning Python but the read is slow, After instructions to install the full Anaconda Python, your are on Page 78 of the Kindle Cloud Reader PC web version before you get to section 1.5.1 using IPythod Interactive Mode. You have to find out how to get to Anaconda Prompt ( Hint use the computer search function to find a prompt) To run the first example of Rolling Dice you have to read the extra instructions from Git Hub, Why the book was not updated about this make me wonder about the rest of the book, and should I continue? The answer is yes, I purchase the book to get a good foundation. Using the Anaconda version just makes it easy to get up to speed on the learning and computer setup consider these 3 stars for Chapter 1 only.

This is one of the only technical books that I've thrown into the trash. I have a Master's degree and have worked on several commercial products using low-level programming languages. I wanted to learn Python and ended up with this book because of hype and a low price. The book continues to sell itself on every page with frequent references to Big Concepts that you're not actually learning. What it actually teaches is how to use Anaconda to install stuff. For example, near the end of the book there is an example of how to type a "conda" command to create a "conda environment" with a long list of big libraries in it such as tensorflow and numpy, but nowhere does the book tell how to create an environment the standard python way (with the standard python modules venv or virtualenv). At that point near the end of the book it is still explaining that you have to hit the return key after typing a command in the terminal. I quickly learned much more using "Whirlwind Tour of Python" and "Learning Python" and can get my work done. If you have the freedom to choose any book, don't choose this one.

This is a huge book with a cocktail of information on Python and almost anything else related to Machine Learning and Natural Language Processing.A bit hard to follow, but interesting and useful if chapters read separately.**Later Edit** I'll switch to 5-stars because - compared to other books I've read lately - this one is close to exceptional with most of the information it contains. The first half is a manual on the Python language, and IMHO this should have been in a separate book.The second part covers, in separate chapters, important areas from AI:o Natural Language Processing - with TextBlot…o Data Mining - with Twittero Cognitive Computing - with IBM Watsono Machine Learning - with Classification, Regression and Clusteringo Deep Learning - with Keras, TensorFlow etco Big Data - with Hadoop, Spark, NoSQL and IoTThese last chapters alone are rather short, but pure gold. If you don't have time to read the equivalent of several books on AI, each covering one of these topics, these quick references are good enough to give you a good idea where we are.

The book is well written and informative. Concrete examples are provided to leverage and test your knowledge of the subject matter. I received the book for free to review and I ended up buying a copy for myself as a gift to my nephew majoring in engineering. The topics are discussed in a user friendly and relate able way.

I love the Deitel books. Their Java book is or was the best and this Python tome is the same. This book is for real programmers.

Poorly organized topics, difficult to find important points quickly. Required for a class, otherwise would not have purchased. Much better publications out there from Sweigart, others. Of note: this book may be better suited for very advanced coders, but it skims over the more common subjects quickly and poorly.

The product and the seller ar good, but the letters are very small.

Total disappointment with this book

Libro perfetto ottima fattura e contiene tantissimi concetti per programmare in python.

Excelente livro, com conteúdo apresentado de modo didático e pratico

Contenido práctico y bien estructurado. Aborda los temas de una manera amigable para el lector.El contenido es bastante amplio para todo aquel que se involucre a la ciencia de datos y el machine learning.