Search result for Mathematics for machine learning: pca Online Courses & Certifications
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Mathematics for Machine Learning: PCA
by Marc Peter Deisenroth- 4
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Approx. 18 hours to complete
Using all these tools, we'll then derive PCA as a method that minimizes the average squared reconstruction error between data points and their reconstruction. However, this type of abstract thinking, algebraic manipulation and programming is necessary if you want to understand and develop machine learning algorithms. Heading for the next module!...
Fundamentals of Machine Learning in Finance
by Igor Halperin- 3.8
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Approx. 18 hours to complete
Fundamentals of Machine Learning in Finance will provide more at-depth view of supervised, unsupervised, and reinforcement learning, and end up in a project on using unsupervised learning for implementing a simple portfolio trading strategy. Introduction to Fundamentals of Machine Learning in Finance PCA for Stock Returns, Part 1 PCA for Stock Returns, Part 2...
Python and Machine Learning for Asset Management
by John Mulvey - Princeton University , Lionel Martellini, PhD- 3
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Approx. 17 hours to complete
Machine Learning for Investment Decisions: A Brief Guided Tour References for module 1"Introducing the fundamentals of machine learning" Machine learning techniques for robust estimation of factor models References for module 2"Machine learning techniques for robust estimation of factor models" Machine learning techniques for efficient portfolio diversification Machine learning techniques for regime analysis...
Fundamentals of Machine Learning with Python Implementation.
by Three Millennials- 3.5
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7 hours on-demand video
Learn Fundamentals of Machine Learning from scratch to make students well equipped with all basics and math involved Hello there! Welcome to Fundamentals of Machine Learning with Python Implementation. Deciding which algorithm fits for a given problem Use Python for Data Science and Machine Learning Know which Machine Learning model to choose for each type of problem...
$12.99
Big Data Applications: Machine Learning at Scale
by Alexey A. Dral , Vladimir Lesnichenko , Evgeny Frolov , Ilya Trofimov , Pavel Mezentsev , Emeli Dral- 3.8
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Approx. 28 hours to complete
Machine learning is transforming the world around us. To become successful, you’d better know what kinds of problems can be solved with machine learning, and how they can be solved. - build and apply linear models for classification and regression tasks; Machine Learning Applications for BigData (Optional) Machine Learning: Introduction Basic RecSys for Data Engineers...
Principal Component Analysis (PCA) and Factor Analysis
by Gopal Prasad Malakar- 4.3
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1.5 hours on-demand video
Analytics / Machine Learning / Dimensionality Reduction : PCA & Factor Analysis using SAS and R program Properties of Principal ComponentsSummarize PCA conceptsUnderstand why first eigen value is bigger than second, second is bigger than third and so onData Treatment for conducting PCA Conduct PCA using SAS: UnderstandCorrelation MatrixEigen value tableScree plotHow many pricipal components one should keep?...
$9.99
Data Science 2021 : Complete Data Science & Machine Learning
by Jitesh Khurkhuriya- 4.6
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25.5 hours on-demand video
Mathematics for Machine Learning including Linear Algebra, Calculus and how it is applied in Machine Learning Algorithms as well as Data Science Advance Mathematics for Machine Learning Mathematics is the very basis for Data Science in general and Machine Learning in particular. Learn complete Mathematics of Linear Algebra, Calculus, Vectors, Matrices for Data Science and Machine Learning....
$14.99
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Data Science for AI and Machine Learning Using Python
by Shiv Onkar Deepak Kumar- 3.9
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9.5 hours on-demand video
The whole concepts of the course are to make you ready for Data Science projects, mainly in Machine learning and AI projects. Foundation of Machine learning Supervised Machine learning - Regression Supervised Machine learning - Classifications Unsupervised Machine learning (Clustering, KNN, PCA)...
$12.99
Mathematics for Machine Learning: Multivariate Calculus
by Samuel J. Cooper , David Dye , A. Freddie Page- 4.7
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Approx. 18 hours to complete
This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We then start to build up a set of tools for making calculus easier and faster. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future....
Mathematics for Machine Learning: Linear Algebra
by David Dye , Samuel J. Cooper , A. Freddie Page- 4.7
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Approx. 19 hours to complete
At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning. Introduction to Linear Algebra and to Mathematics for Machine Learning Introduction: Solving data science challenges with mathematics...
