Teaching & Academics Math Linear Algebra

Linear Algebra for Data Science & Machine Learning - 2020

Learn Basics of Linear Algebra (Mathematics) for Artificial Intelligence, Machine Learning and Data Science
Rating: 3.6 out of 5 (27 ratings)
3,552 students
Created by Datai Team Academy
Enroll now
Linear Algebra for Data Science & Machine Learning - 2020
Rating: 3.6 out of 5 (27 ratings)
3,554 students
Buy now
Basics of Linear Algebra for Machine Learning & Data Science
Scalar & Vector Arithmetic
Linear Equations
Matrices - Tensors

Requirements

  • No prior knowledge is required
  • Aim of Learning Machine Learning and Data Science

Description

LINEAR ALGEBRA for DATA SCIENCE & MACHINE LEARNING COURSE DESCRIPTION

  • Why Learn Linear Algebra?

  • Sets

  • Linear Equation Systems

  • What is a Scalar?

  • Scalar & Vector Arithmetic

  • Vector Addition and Subtraction

  • Scalar Multiplication of Vectors

  • Dot & Cross Product

  • Dot Product Linear Algebra Style

  • Vector Subspace

  • Linear Combinations of Vectors

  • Span

  • Linear Dependence and Independence

  • Solving Systems of linear equations

  • Linear Equation Example

  • Generating Set and Basis

  • Linear Mapping/Linear Transformation

  • Additivity

  • Homogeneity

  • Kernel

  • Matrices - Tensors

  • Matrix Multiplication

  • Range of a Matrix

  • Kernel of a Matrix

  • Determinant of a Matrix

  • Identity , Transpose and Inverse Matrix

  • Eigenvector and Eigenvalue

WHY LINEAR ALGEBRA?

  • Linear algebra is absolutely key to understanding the calculus and statistics you need in machine learning and data science.

  • If you can understand machine learning methods at the level of vectors and matrices you will improve your intuition for how and when they work.

  • A deeper understanding of the algorithm and its constraints will allow you to customize its application and better understand the impact of tuning parameters on the results.

THE OPPORTUNITIES YOU WILL HAVE WITH THIS COURSE

  • In-class support: We don't just give you video lessons. We have created a professional Python Programmer team and community to support you. This means that you will get answers to your questions within 24 hours.

WHO WE ARE: DATAI TEAM ACADEMY

DATAI TEAM is a team of Python Programmers and Data Scientists.

Let's register for the course and start to Linear Algebra for Data Science & Machine Learning.

Who this course is for:

  • Those who want to specialize in Machine Learning but not know linear algebra
  • Those who want to learn a linear algebra but cannot decide where to start
  • Those who want to start and continue their education or career in data science, machine learning or artificial intelligence

Course content

1 section • 7 lectures • 1h 25m total length
  • Extra Resources
    00:04
  • Section 1
    23:45
  • Section 2
    15:30
  • Section 3
    14:29
  • Section 4
    20:44
  • Section 5
    11:03
  • BONUS
    00:00

Featured review

Yasmin Muhammad Elias
Yasmin Muhammad Elias
615 courses
54 reviews
Rating: 5.0 out of 53 weeks ago
Oustanding course for the foundation basis of Data Science. Amazing Illustrations and carries every bit of detail needed for the fundamental Basis of Mathematics in Linear Algebra. The instructor has covered the course comprehensively, clearly, and in a very systematic approach and leadership in Linear Algebra.

Instructor

Datai Team Academy
Artificial Intelligence & Data Science
Datai Team Academy
  • 3.7 Instructor Rating
  • 65 Reviews
  • 4,943 Students
  • 6 Courses

Artificial Intelligence & Data Science

We combine the lessons that we have prepared with our interest and expertise on Python, Data Science, Machine Learning, Deep Learning and Artificial Intelligence with real life examples. In addition, we encourage you to share your work with the world to extend the knowledge you have learned beyond the basic level.

Thanks to our success on the Kaggle platform, a subsidiary of Google, we teach you professional and world class quality certified lessons.

Add the courses you need to your library now and let's get started!