- 4 Free Math Courses to do and Level up your Data Science Skills - Jun 22, 2020.
Just as there is no Data Science without data, there's no science in data without mathematics. Strengthening your foundational skills in math will level you up as a data scientist that will enable you to perform with greater expertise.
- Top KDnuggets tweets, May 13-19: Linear algebra and optimization and machine learning: A textbook - May 21, 2020.
Also: Everything you need to become a self-taught #MachineLearning Engineer ; SQL Cheat Sheet (2020) - a useful cheat sheet that documents some of the more commonly used elements of SQL;
- Linear algebra and optimization and machine learning: A textbook - May 18, 2020.
This book teaches linear algebra and optimization as the primary topics of interest, and solutions to machine learning problems as applications of these methods. Therefore, the book also provides significant exposure to machine learning.
- A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM) - Mar 18, 2020.
Support Vector Machines (SVMs) are powerful for solving regression and classification problems. You should have this approach in your machine learning arsenal, and this article provides all the mathematics you need to know -- it's not as hard you might think.
- 10 Free Must-See Courses for Machine Learning and Data Science - Nov 8, 2018.
Check out a collection of free machine learning and data science courses to kick off your winter learning season.
- New Book: Linear Algebra – what you need for Machine Learning and Data Science now - Oct 24, 2018.
From machine learning and data science to engineering and finance, linear algebra is an important prerequisite for the careers of today and of the future. Learn the math you need with this book.
- Boost your data science skills. Learn linear algebra. - May 3, 2018.
The aim of these notebooks is to help beginners/advanced beginners to grasp linear algebra concepts underlying deep learning and machine learning. Acquiring these skills can boost your ability to understand and apply various data science algorithms.