Faisalsardar1

$25.99

stanford machine learning course (half course + summary)

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• 16 artículos •
por faisalsardar1 •
subido 2022

i x

Supervised learning setup • Notas de lectura
Dataset split; Exponential family. Generalized Linear Models. • Resumen
Linear Algebra Review • Notas de lectura
Linear Algebra • Presentación
Gaussian discriminant analysis. Naive Bayes.Laplace Smoothing. • Notas de lectura
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Python/Numpy Tutorial.

$5.99

Text editor/IDE options.. (don’t settle with notepad) • PyCharm (IDE) • Visual Studio Code (IDE) • Sublime Text (IDE) • Atom • Notepad ++/gedit • Vim (for Linux)

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Presentación
• 39 páginas •
por faisalsardar1 •
subido 2022

i x

Stanford University • machine learning ml
machine learning course • Por faisalsardar1

Neural Networks

$6.49

Deep Learning Supervised learning with non linear models Logistic Regression Neural Networks computational power data available algorithms Propagation equation

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Resumen
• 6 páginas •
por faisalsardar1 •
subido 2022

i x

Stanford University • machine learning ml
machine learning course • Por faisalsardar1

Neural Networks

Gratis

Deep Learning Supervised Learning with Non-linear Models Neural Networks Backpropagation Vectorization Over Training Examples

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Notas de lectura
• 21 páginas •
por faisalsardar1 •
subido 2022

i x

Stanford University • machine learning ml
machine learning course • Por faisalsardar1

Kernels, SVM.

$6.99

summary of Kernel Methods SVMs

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Resumen
• 8 páginas •
por faisalsardar1 •
subido 2022

i x

Stanford University • machine learning ml
machine learning course • Por faisalsardar1

Kernel Methods

Kernels. SVM.

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Notas de lectura
• 30 páginas •
por faisalsardar1 •
subido 2022

i x

Stanford University • machine learning ml
machine learning course • Por faisalsardar1

Probability Theory

$11.99

Outline 1 Basics 2 Random Variables 3 Expectation-Variance 4 Joint Distributions 5 Covariance 6 RV Conditionals 7 Random Vectors 8 Multivariate Gaussian

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Presentación
• 100 páginas •
por faisalsardar1 •
subido 2022

i x

Stanford University • machine learning-ml
machine learning course • Por faisalsardar1

The Multivariate Gaussian Distribution

$4.99

a multivariate normal (or Gaussian) distribution 1 Relationship to univariate Gaussians 2 The covariance matrix 3 The diagonal covariance matrix case 4 Isocontours 5 Linear transformation interpretation

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Notas de lectura
• 10 páginas •
por faisalsardar1 •
subido 2022

i x

Stanford University • machine learning-ml
machine learning course • Por faisalsardar1

Probability Theory Review

Gratis

Probability theory is the study of uncertainty. Through this class, we will be relying on concepts from probability theory for deriving machine learning algorithms. These notes attempt to cover the basics of probability theory at a level appropriate for CS 229. The mathematical theory of probability is very sophisticated, and delves into a branch of analysis known as measure theory. In these notes, we provide a basic treatment of probability that does not address these finer details. 1 Elem...

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Notas de lectura
• 12 páginas •
por faisalsardar1 •
subido 2022