I was working today in the deployment of a small neural network model prototype converted to Core ML to be used in an iPhone app.
I was trying to find the best way to get things to work and then it occurred to me I had solved a similar issue before… where‽ when‽ aha!
The answer was actually in my Advanced Data Science and Analytics with Python.
I was not expecting this today, but I am very pleased to see that my first physical copies of “Advanced Data Science and Analytics” have arrived. I was working under the assumption that these would not be sent until after lockdowns were lifted, but that was not the case.
I am very happy to see the actual book and hold it in my hands!
I also hear that individual copies have started arriving to their new owners. If you ordered yours, let me know when it arrives. I will post your pictures!
It is official! “Advanced Data Science and Analytics with Python” is published!
According to the information I had received from CRC Press, my publisher, the book would be available on May 7th. According to the official page of the book the volume was available since May 5th.
So if you have already preorder, your copies may be on their way soon. If not, you can definitely get your copy either with CRC Press, or Amazon.
Looking forward to hearing what you think of the book.
I am reaching out as volume 2 of my data science book will be out for publication in May and my publisher has made it possible for me to offer 20% off. You can order the book here.
This follows from “Data Science and Analytics with Python” and both books are intended for practitioners in data science and data analytics in both academic and business environments.
The new book aims to present the reader with concepts in data science and analytics that were deemed to be more advanced or simply out of scope in the author’s first book, and are used in data analytics using tools developed in Python such as SciKit Learn, Pandas, Numpy, etc. The use of Python is of particular benefit given its recent popularity in the data science community. The book is therefore a reference to be used by seasoned programmers and newcomers alike and the key benefit is the practical approach presented throughout the book
More information about the first book can be found here.
Well, this are the final corrections for my latest book “Advanced Data Science and Analytics with Python“. Next stop publication!
Super excited to have received the proofread version of Advanced Data Science and Analytics with Python. They all seem to be very straightforward corrections: a few missing commas, some italics here and there and capitalisation bits and bobs.
I hope to be able to finish the corrections before my deadline for March 25th, and then enter the last phase before publication in May 2020.
I have received the latest information about the status of my book “Advanced Data Science and Analytics with Python”. This time reviewing the latest cover drafts for the book.
This is currently my favourite one.
Awaiting the proofreading comments, and I hope to update you about that soon.
If you are interested in #DataScience you surely have heard of #pandas and you would be pleased to hear that version 1.0 finally out. With better integration with bumpy and improvements with numba among others. Take a look!
— Read on www.anaconda.com/pandas-1-0-is-here/
It was great to invited to give the joint Physics Astronomy and Maths + Computer Science research seminar today at the University of Hertfordshire. I had a good opportunity to meet old colleagues and meet new faculty. There were also many students and they with many questions.
I was glad to hear they are thinking about offering more data science courses and even a dedicated programme. I would definitely be interested to hear more about that.
There you go, the first checkpoint is completed: I have officially submitted the completed version of “Advanced Data Science and Analytics with Python”.
The book has been some time in the making (and in the thinking…). It is a follow up from my previous book, imaginatively called “Data Science and Analytics with Python” . The book covers aspects that were necessarily left out in the previous volume; however, the readers in mind are still technical people interested in moving into the data science and analytics world. I have tried to keep the same tone as in the first book, peppering the pages with some bits and bobs of popular culture, science fiction and indeed Monty Python puns.
Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow up from the topics discuss in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The development is also supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications.
The book can be read independently form the previous volume and each of the chapters in this volume is sufficiently independent from the others proving flexibiity for the reader. Each of the topics adressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book
Time series analysis, natural language processing, topic modelling, social network analysis, neural networds and deep learning are comprehensively covrered in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users fingertips in the form of an iPhone app.
While the book is still in the oven, you may want to take a look at the first volume. You can get your copy here:
Furthermore you can see my Author profile here.