Math Vs Coding: Data Science
- If I know the entire math logic for machine learning algorithms, but I could not code well, do I stand a chance to enter the data science field?
- If I just barely know the math behind those machine learning algorithms, but I can code well, am I qualified enough to be a data scientist?
- Thus, having knowledge in different programming languages is definitely a plus so that you could save your time on writing the whole code in Python in order to train the model.
- Mathematics and coding are equally important in data science, but if you are considering to switch or start your career in the data science field, I would say coding or programming skills are more important than deep dive to the math for various kinds of machine learning models.
- His experiences involved more on crawling websites, creating data pipeline and also implementing machine learning models on solving business problems.
Mathematics for Machine Learning (free PDF book)
- Companion webpage to the book "Mathematics for Machine Learning".
- Copyright 2019 by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong. To be published by Cambridge University Press.
- Please link to this site using https://mml-book.com.
- Twitter: @mpd37, @AnalogAldo, @ChengSoonOng. We wrote a book on Mathematics for Machine Learning that motivates people to learn mathematical concepts.
- The book is not intended to cover advanced machine learning techniques because there are already plenty of books doing this.
- Instead, we aim to provide the necessary mathematical skills to read those other books.
- The book will be published by Cambridge University Press in early 2020.
- We aim to keep this book fairly short, so we don’t cover everything.
- We will keep PDFs of this book freely available after publication.
- We submitted the final draft for copy-editing.
- Therefore, any issues you raise now may not make it into the printed version.
I bought an expensive purse in high school, then my dad showed me how I could have grown that money instead — and I've lived by the lesson ever since
- The compound interest formula takes into account more information than simply the principal amount you invest, the rate of return, and the time period of investment.
- For example, let's say you'd like to invest $10,000 at an annual interest rate of 3%, compounded monthly for 20 years.
- That's what you have to begin with, and to find out what you'll end up with, we need to account for the combined effect of your interest rate divided by the number of times the interest is compounded per year (12, for compounding monthly) and then exponentially raise that to the total number of times your interest is compounded.
- With a basic understanding of the mathematics of compound interest as well as a familiarity with our banking system, I was fortunate to learn how to take advantage of high-yield accounts and favorable interest at a very young age.
How Randomness Can Arise from Determinism
- For a Galton board with any given number of rows, the number of different paths a marble can take to reach a bin placed at a given row is exactly equal to the corresponding number in Pascal’s triangle (as shown below).
- In a traditional Galton board, the marble distribution in every row is highest in the center and falls off toward the ends.
- In a traditional Galton board, the final position of an individual marble as it moves from about the middle row to the bottom is not very predictable — it could end up in any of the bins.
- It’s as if the universe splits every time a marble goes left or right in a Galton board, just because we are ignorant of the exact details of the marble-peg interaction.