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Python/Numpy Tutorial.
Last document update:
ago
Text editor/IDE options.. (don’t settle with notepad)

• PyCharm (IDE)

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• Sublime Text (IDE)

• Atom

• Notepad ++/gedit

• Vim (for Linux)
Deep Learning

Supervised learning with non linear models

Logistic Regression

Neural Networks

computational power

data available

algorithms

Propagation equation
Deep Learning

Supervised learning with non linear models

Logistic Regression

Neural Networks

computational power

data available

algorithms

Propagation equation
Deep Learning

Supervised Learning with Non-linear Models

Neural Networks

Backpropagation

Vectorization Over Training Examples
Deep Learning

Supervised Learning with Non-linear Models

Neural Networks

Backpropagation

Vectorization Over Training Examples
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...
Probability Theory Review
Last document update:
ago
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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