The Importance of being earnest is my favorite play and this post is a small tribute to the book – “The Importance of Knowing Mathematics”.
I was reading Bill Gates’ fireside chat with Jessie Woolley-Wilson. It’s named “A fireside chat on Education, technology, and almost everything in Between”. The article prompted me to reflect on my relationship with Mathematics and how it has changed over the years.
In the article, Bill Gates emphasized why maths matters more than ever. Data being the key in almost every organization, role, and discipline, the knowledge of statistics and maths concepts is becoming vital.
I was never very fond of mathematics while growing up, primarily because of the way it was taught. I would focus on memorizing formulas and methods of solving to score high in exams. Even if I didn’t understand the utility and application, I felt confident as long as I scored high. This continued throughout my undergrad as well. In mechanical engineering, there was quite a bit of application but I was fixated only on grades.
It was only after I started getting involved in Data Science and Machine Learning, that I realized the beauty of calculus and linear algebra. A big role in the change in my perspective were youtube educators (3B1B, Khan Academy, etc.), and my Professors at Duke.
All this leads me to think that if maths is an important skill, how can we make the younger generation grasp it better and disassociate the fun from grades?
My love for Maths increased exponentially once I started being creative with mathematics.
I am sure when I say creativity, maths is the last discipline that will come to your mind. Its taught as a dull discipline and used by standardized test makers to assess calculation skills. This was exactly the reason why I could never be creative with Maths. It was about learning formulae, learning shortcuts to calculate faster, and learning very complicated concepts that were neither necessary nor useful at my age (Hi JEE!).
I gave maths another chance. I learned machine learning and concepts associated with statistics. It started in the same way mentioned above, but this time, I wasn’t taking standardized tests and was able to apply my creativity with data and deliver solutions. When I associated maths with business outcomes, it became even more fun. It wasn’t about one correct answer. It was about exploring and optimizing.
If I were to go back in time, I would probably suggest myself think of maths as a beautiful tool that can be used creatively to find unique solutions to real-world problems.
Mathematics and Data Science
One of the most frequent questions people ask me before getting into Data Science is: How important is maths for data science?
My short answer is: It’s very much necessary if you want to become a successful professional in data science, combined with good communication and coding skills.
Mathematics forms the backbone of data science. It is the language used to understand the algorithms and models that are used to analyze and interpret data. From basic arithmetic to advanced calculus, linear algebra, statistics, and probability theory, math is the key to unlocking the potential of data.
At every stage of the data science process, mathematical concepts are used. Data cleaning and preparation require mathematical skills to ensure that the data is accurate and ready for analysis. Without a strong foundation in math, it is difficult to understand and implement these models, which can hinder the ability to make accurate predictions and uncover insights.
By using mathematical concepts and language, data scientists can present their findings clearly and concisely, making it easier for stakeholders to understand and act upon the insights. This is especially important in industries like finance or healthcare where even small errors can have significant consequences.
To summarize,
Maths + Coding + Business Understanding + Communication = Successful Data Science Career.
Three most important Mathematics topics for Data Science
1. Probability and Statistics
Probability theory is the branch of mathematics that deals with the likelihood of events occurring, while statistics is the branch that deals with the analysis of data. These two subjects provide a framework for understanding the reliability of data and insights.
2. Linear Algebra
Linear algebra is the branch of mathematics that deals with linear equations, matrices, and vectors. It helps in understanding the mathematical concepts behind machine learning algorithms, such as principal component analysis and singular value decomposition.
3. Calculus
Calculus is the branch of mathematics that deals with rates of change and accumulation. It is important for optimization and gradient descent algorithms, which are widely used in machine learning.
My favorite books on Mathematics
1. Naked Statistics by Charles J. Wheelan
I read this book in 2021 and I have never looked at Statistics the same way. The book highlights the high applicability of maths to solve real-world problems and also emphasizes the way it can be misused.
After reading the book, I couldn’t stop thinking about a histogram shown on TV about the approval rate of the ruling government. The approval rate was around 46% and in the graph, this was shown in green color and as a higher bar, twisting the facts associated with the number. Media is notoriously the leader in misusing stats. Love this book for debunking the misconceptions.
2. Statistics without tears by Derek Rowntree
First, I love the name of this book. Second, the way it simplifies the stats concepts is amazing. I read this book in 2021 when I started my Masters’s degree and it has been so helpful in my academics and professional work. I am rarely blank on steps to follow to get information from data.
3. Math Without Numbers by Milo Beckman
Trust me, the only numbers in the books you will see are the page numbers!
This book flows like a conversation and doesn’t overwhelm you with intricate jargon that maths is very well known for. It blurred the boundaries in my head between maths and creativity and solidified the concepts of maths. I had always struggled with topology in school and college, but this book changed it for me.
I hope this post has helped alleviate your stress related to mathematics.