Download Python, Matrices, and Linear Algebra for Data Science and ML

What you would learn in Python, Matrices, and Linear Algebra for Data Science and ML course?

The course introduces students to fundamental concepts in linear algebra and Python that are essential as a basis for understanding the fundamentals of machine learning and data science. The focus is on making lectures in a manner that includes both geometrical insights as well as a computational application of the fundamental notions in linear algebra. In addition, all of the concepts are discussed and implemented using the Python programming framework. The following topics will be discussed:

1. Introduction to Python

2. Matrices and Vectors are used in Data Science and Machine Learning

3. Vector and Matrices Operations

4. Computing Eigenvalues

5. Computing Singular Values

6. Mathematical Operations on Matrix within Machine Learning Algorithm

7. Python Data Science and Machine Learning Libraries

Who is this course intended for:

• Students who wish to master linear algebra and Python programming concepts

• Students who wish to build fundamentals in linear algebra to prepare for Data Science, Machine Learning as well as Deep Learning domains

• Everyone is interested in understanding python and wants to develop an understanding of the basic concepts of linear algebra.

• Data researchers and students in machine learning who are looking to review their fundamentals in the area of linear algebra

• Anyone interested in learning Python to study machine learning, data science, and AI domain

Course Content:

• 1. Introduction to Python
• 2. Matrices and Vectors are used in Data Science and Machine Learning
• 3. Vector and Matrices Operations
• 4. Computing Eigenvalues
• 5. Computing Singular Values
• 6. Matrix Machine Learning Operations Algorithm
• 7. Python Data Science and Machine Learning Libraries

Download Python, Matrices, and Linear Algebra for Data Science and ML from below links NOW!