Foundations of Math & Stats for Machine Learning and AI

Foundations of Math & Stats for Machine Learning and AI

EDUCBA Bridging the Gap

Last Updated on January 25, 2024 by GeeksGod

Course : Mathematics & Statistics Foundations | Machine Learning & AI

Free Udemy Coupon – Learn Machine Learning

The future for AI is extremely promising and it isn’t far from when we have our own robotic companions. This has pushed a lot of developers to start writing codes and start developing for AI and ML programs. However, learning to write algorithms for AI and ML isn’t easy and requires extensive programming and mathematical knowledge. Mathematics forms the core of data science and machine learning. Thus, to be the best data scientist you can be, you must have a working understanding of the most relevant math.

Getting started in data science is easy thanks to high-level libraries like Scikit-learn and Keras. However, understanding the math behind the algorithms in these libraries opens an infinite number of possibilities up to you. From identifying modeling issues to inventing new and more powerful solutions, understanding the math behind it all can dramatically increase the impact you can make over the course of your career.

The Importance of Mathematics in Machine Learning

Mathematics, Probability & Statistics are the bedrock of modern science such as machine learning, predictive risk management, inferential statistics, and business decisions. In this highly comprehensive Mathematics, Statistics, and Probability course, you will learn everything from Set theory, Combinatorics, Probability, statistics, and linear algebra to Calculus with tons of challenges and solutions for Business Analytics, Data Science, Data Analytics, and Machine Learning.

Mathematics form the basis of almost all the Machine Learning algorithms. Without maths, there is no Machine Learning. Machine Learning uses mathematical implementation of the algorithms and without understanding the math behind it is like driving a car without knowing what kind of engine powers it.

Improve Your Math Skills for Machine Learning

You may have studied all these math topics during school or universities and may want to freshen it up. However, many of these topics, you may have studied in a different context without understanding why you were learning them. They may not have been taught intuitively or though you may know the majority of the topics, you cannot correlate them with Machine Learning.

This course of Math For Machine Learning, aims to bridge that gap. We will get you up to speed in the mathematics required for Machine Learning and Data Science. We will go through all the relevant concepts in great detail, derive various formulas and equations intuitively.

Mathematics Topics Covered in This Course
  • Algebraic Equations
  • Linear Algebra
  • Calculus including Gradient using Single and Double order derivatives
  • Vectors and Matrices
  • Probability and much more

By the end of this course, you will have a strong foundation in mathematics, which will enhance your understanding and implementation of Machine Learning algorithms. You will be able to apply your mathematical knowledge to develop more effective and accurate ML models. Don’t miss the opportunity to improve your math skills and take advantage of the endless possibilities in the field of machine learning.

Get Started with Machine Learning Today – Enroll in This Free Udemy Coupon Course!

Machine learning is revolutionizing the world and you can be a part of it. Start learning the math behind machine learning today and unlock your true potential. Enroll in this Machine Learning course now and use the Free Udemy Coupon code to get started for free. Don’t miss out on this amazing opportunity to enhance your knowledge and skills in the field of machine learning.

Udemy Coupon :


What you will learn :

1. Understand and implement Regression, Classification, and Clustering algorithms
2. Learn Linear Algebra, Calculus for Machine and Deep Learning
3. Build Mathematical intuition especially Calculus required for Deep learning, Data Science and Machine Learning
4. Refresh the mathematical concepts for AI and Machine Learning

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