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Python/Numpy Tutorial.
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Text editor/IDE options.. (don’t settle with notepad)

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• Atom

• Notepad ++/gedit

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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
Do you wonder why so many students wear nice clothes, have money to spare and enjoy tons of free time? Well, they sell on Stuvia! Imagine your study notes being downloaded a dozen times for $15 each. Every. Single. Day.
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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