We at AI Time are here to bring you an article purely based on Book recommendations. We have been blessed to have the opportunity to speak to some moving and inspirational people in the tech world, from data scientists to CEO of data companies.
I will cover different books which will cater to different areas in the tech world. If you are reading this article, I assume that you have an interest in the technology field, whether it is Data Science, Artificial Intelligence, etc. I hope this will steer you in the right direction and help you build your current career or be the stepping stone in you entering a new one.
So let’s start…
The first interview I conducted at AI Time Journal was with Kristen Kehrer and it was so moving to see another female in the industry and inspiring to see how far she has come. During the interview, she recommended a book called ‘Weapons of Math Destruction: How Big Data Increases Inequality and Threatens’ by Cathy O’Neil. Cathay O’Neil is a mathematician, data scientist, and author. She is the founder of mathbabe.org and Weapons of Math Destruction is a New York Times best-seller. If you have a look at her blog mathbabe.org, she explores topics that I believe happen in everyday conversations but is never really brought to the forefront for change. I highly respect her work and appreciate the effort she has gone to in order to be a voice.
“Big Data processes codify the past. They do not invent the future.”– Weapons of Math Destruction
Weapons of Math Destruction explores the impact of algorithms on society and they may be causing a controversy in the already existence of inequality. She decided to explore this when she was working as a Quantitative Analyst on Wall Street and saw first-hand how maths was used to cause some of the well-known financial crises’, which affected many people’s lives where some are only recovering from it now. A rigged financial/baking system? That’s definitely a topic that many of us have had with peers, colleagues, and family members. If you are someone who works in the finance department and want to transition into learning a programming language to better your career or you are someone who enjoys money talk, banking industry, I would highly recommend this book. It is a great insight into other people’s personal experience and their take on algorithms.
Founder of Integrated Machine Learning and AI Thom Ives, dropped us a gem when he recommended this book. If you are a newbie into the tech world like me, learning about data never stops in your early years. There is so much to learn and the world of technology is constantly evolving. Machine Learning by Tom Mitchell includes chapters from Decision Tree Learning, Artificial Neural Networks, and Genetic Algorithms.
“A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”– Tom Mitchell
People say that the use of data in artificial intelligence was discovered in the 1950’s, this book was written in 1997. As I said, the use of data and what we can do with it is changing daily as the evolution of technology continues. If you are like me and you’re interested in how people’s theories and opinions change over time, I believe this would be a good read. It is interesting to see how far the world of technology has changed, the way people learned from 20 years ago to now. Even look back at your learning days and compare them to now. I was born in the ’90s but the evolution of education has evolved so fast that I can’t keep up.
This book is a good introduction to all types of machine learning algorithms and provides an excellent theoretical grounding in how many machine learning models are put together. If you want to learn more about machine learning and need a steady introduction, this may be the book for you.
AI Time Journal conducted an interview with Susan Walsh, Founder/MD of The Classification Guru, LTD. In her interview, she had many book recommendations and one of them included Telling Your Data Story by Scott Taylor who is also known as the Data Whisperer. He has over 25 years of experience in master data, metadata, MDM, and solving data management challenges for large global enterprises.
His book ‘Telling Your Data Story’ is a practical guide to diving into the strategic value of data management. He explores the power of data management and how it’s used in our everyday lives from customer interaction, data analysts, and scientist project work to help some of the most successful big companies to be in the position they are in now. He helps companies navigate in the right direction of strategic rationale and business alignment and how the benefits a company more than technical implementation.
From business leaders to data operatives, this book will help you manage your firm efficiently whilst also being able to get into the minds of business leaders and decision-makers. This book is not highly technical and does not confuse you with terminology that only people who work in data understand. I appreciate that Scott Taylor has blessed us with a book that allows people from different walks of life and careers to understanding the strategic importance of data management. He says: “I want to help you simplify the complex to make sure your enterprise data story ends happily ever after.”. I guess that’s the reason they call him the Data Whisperer.
These 3 books give different approaches from getting into data science, simply understanding data management, and a bit more controversial of what data is actually doing to society. So take your pick and when you have had a read, we at AI Time Journal would love to hear your feedback.
If you would like us at AI Time Journal to further explore something of your interest or have any further questions, please connect with us on LinkedIn or Twitter.
A young data scientist, who wishes to explore the different ways that Artificial Intelligence can help benefit the longevity of human life and conquer terminal illnesses. I would also like to explore peoples opinions on Artificial Intelligence and what they believe it brings or does not bring to the table. There are so many unanswered questions, which I would like to get more insight on.