6 Math Foundation to Start Learning Machine Learning
Keep reading for FREE
Machine Learning is a tool that Data scientists use to obtain valuable patterns. Learning the math behind machine learning could give you an edge.
These six math subjects are the foundation for machine learning.
Linear Algebra in machine learning is a systematic representation of data that computers can understand.
Training a machine learning model is about finding a good set of parameters. The best value is the minimum value.
Calculus is concerned with a perpetual change that consists of functions and limits. Vector calculus involves the differentiation and integration of the vector fields.
Analytic geometry is concerned with defining and representing geometrical shapes numerically. It extracts numerical information from the shapes numerical definitions and representations.
Important terms that will help you start learning this subject:
Probability is the study of randomness. Probability distribution is a function that measures the probability of a specific outcome associated with the random variable.
Probability theory and statistics are about different aspects of uncertainty.
Matrix decomposition is about how to reduce a matrix into its constituent parts. It tries to simplify complex matrix operations on the decomposed matrix instead of the original matrix.
There are many ways to decompose a matrix using a range of different techniques.
reading habits, gather your
remember what you readand stay ahead of the crowd!
Save time with daily digests
No ads, all content is free
Save ideas & add your own
Get access to the mobile app
4.7 App Rating
Everything in life can teach you a lesson. You just have to be willing to learn.
MORE LIKE THIS