Random thoughts about random subjects… From science to literature and between manga and watercolours, passing by data science and rugby; including film, physics and fiction, programming, pictures and puns.
This survey paper extracts practical considerations from recent case studies of a variety of ML applications and is organized into sections that correspond to stages of a typical machine learning workflow: from data management and model learning to verification and deployment.
In recent years, machine learning has received increased interest both as an academic research field and as a solution for real-world business problems. However, the deployment of machine learning models in production systems can present a number of issues and concerns. This survey reviews published reports of deploying machine learning solutions in a variety of use cases, industries and applications and extracts practical considerations corresponding to stages of the machine learning deployment workflow. Our survey shows that practitioners face challenges at each stage of the deployment. The goal of this paper is to layout a research agenda to explore approaches addressing these challenges.
Right!!! It is early December and this post has been in the inkwell for a few months now. Earlier in the year I received the comments and suggestions from reviewers and the final approval from the excellent team at CRC Press for my 4th book.
After a few weeks of frank procrastination and a few more on structuring the thoughts proposed a bit more, I have got a clear head to start writing. So I am pleased to announce that I am officially starting to write “Statistics and Data Visualisation with #Python”.
“Statistics and Data Visualisation with Python” builds from the ground up the basis for statistical analysis underpinning a number of applications and algorithms in business analytics, machine learning and applied machine learning. The book will cover the basics of programming in python as well as data analysis to build a solid background in statistical methods and hypothesis testing useful in a variety of modern applications.
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!
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
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.
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.