Description
Mathematics for Machine Learning and Data Science Specialization, course Professional Mathematics for Machine Learning and Data Science is published by Coursera Academy. Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. This beginner program is where you will master the basic mathematics of machine learning. Many machine learning engineers and data scientists struggle with mathematics. Challenging interview questions often stop people from advancing in their careers, and even experienced people sometimes feel they lack math skills.
This specialized course uses innovative math pedagogy to help you learn quickly and intuitively, with lessons that use easy-to-use plugins and visualizations so you can see how the math used in machine learning works. Upon completion, you will be familiar with the mathematics of all common algorithms and data analysis techniques, plus the technical know-how to incorporate them into a machine learning career.
At the end of this course, you will learn about the following:
- Represent data as vectors and matrices and identify their characteristics using the concepts of singularity, ranking, and linear independence.
- Using common vector and matrix algebra operations such as dot multiplication, inverse, and determinants
- Expressing certain types of matrix operations as linear transformations
- Using the concepts of eigenvalues and eigenvectors for machine learning problems
- Optimization of various types of functions that are commonly used in machine learning
- Performing gradient reduction in neural networks with different activation and cost functions
- Describing and quantifying the inherent uncertainty in predictions made by machine learning models
- Getting to know the properties of common probability distributions in machine learning and data science
- And….
What you will learn
- Deep understanding of the mathematics of machine learning algorithms
- Statistical techniques that give you the ability to get more information from your data analysis.
- Basic skills that employers want, and will also help you solve machine learning interview questions and land your dream job.
- Represent data as vectors and matrices and identify their characteristics using the concepts of singularity, ranking, and linear independence.
Details of the Mathematics for Machine Learning and Data Science Specialization course
Chapters of Mathematics for Machine Learning and Data Science Specialization course
Course prerequisites
- A high-school level of mathematics and a beginner’s understanding of machine learning concepts will help you get the most out of this class.
Pictures
Sample video
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
Quizzes and labs, etc.: Link 1, Link 2
This educational series consists of 3 separate courses.
Version 2023/11 compared to 2023/2: Added Probability & Statistics for Machine Learning & Data Science course.
The version of 2024/4 compared to 2023/2 has increased the number of 6 lessons and the duration of 1 hour 46 minutes. Also, 34 text files have been added.
download link
Calculus for Machine Learning and Data Science fix
Linear Algebra for Machine Learning and Data Science fix
Probability & Statistics for Machine Learning & Data Science fix
File(s) password: www.downloadly.ir
Size
1.82 GB
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