- Copyright 2022
- Edition: 1st
- ISBN-10: 0-13-790323-5
- ISBN-13: 978-0-13-790323-8
27+ Hours of Video Instruction
An outstanding data scientist or machine learning engineer must master more than the basics of using ML algorithms with the most popular libraries, such as scikit-learn and Keras. To train innovative models or deploy them to run performantly in production, an in-depth appreciation of machine learning theory is essential, which includes a working understanding of the foundational subjects of linear algebra, calculus, probability, statistics, data structures, and algorithms.
When the foundations of machine learning are firm, it becomes easier to make the jump from general ML principles to specialized ML domains, such as deep learning, natural language processing, machine vision, and reinforcement learning. The more specialized the application, the more likely its implementation details are available only in academic papers or graduate-level textbooks, either of which assume an understanding of the foundational subjects.
This master class includes the following courses:
- Linear Algebra for Machine Learning
- Calculus for Machine Learning LiveLessons
- Probability and Statistics for Machine Learning
- Data Structures, Algorithms, and Machine Learning Optimization
Linear Algebra for Machine Learning LiveLessons
provides you with an understanding of the theory and practice of linear algebra, with a focus on machine learning applications.Calculus for Machine Learning LiveLessons
introduces the mathematical field of calculusthe study of rates of changefrom the ground up. It is essential because computing derivatives via differentiation is the basis of optimizing most machine learning algorithms, including those used in deep learning, such as backpropagation and stochastic gradient descent.Probability and Statistics for Machine Learning (Machine Learning Foundations) LiveLessons
provides you with a functional, hands-on understanding of probability theory and statistical modeling, with a focus on machine learning applications.Data Structures, Algorithms, and Machine Learning Optimization LiveLessons
provides you with a functional, hands-on understanding of the essential computer science for machine learning applications.Course Requirements
About Pearson Video Training
- Mathematics: Familiarity with secondary school-level mathematics will make the course easier to follow. If you are comfortable dealing with quantitative informationsuch as understanding charts and rearranging simple equationsthen you should be well-prepared to follow along with all of the mathematics.
- Programming: All code demos are in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples.
Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Sams, and Que. Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.