ICT 10 - 4TH PRELIM Flashcards

1
Q

an open source framework that makes

machine learning and neural networking easier to use

A

Tensorflow

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2
Q

also known as “Tech With Tim”. It will help you to understand TensorFlow and some of its powerful capabilities

A

Tim Ruscica

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3
Q

are at the core of what we call artificial intelligence today. But historically they’ve been hard to understand

A

Neural networks

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4
Q

neural networks, these video courses by

A

Brandon Rohrer

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5
Q

A multi-dimensional matrix and fundamental part of the low-level API

A

Tensor

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6
Q

building a Graph of Ops (operations) that you will run later

A

Graph/ops

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7
Q

how you run the Graph and maintains the state

A

session

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8
Q

is a piece of the graph created by the Ops

A

node

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9
Q

A tensor whose values will typically be in a

continuous range, meaning a single real valued features suffices

A

•Dense Tensor

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10
Q

Actually a group of tensors that make it easier to

represent spread-out or categorical values

A

Sparse Tensor

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11
Q

Often given a set of input data, you will want

to combine or modify input features before you feed them into your network

A

Feature columns

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12
Q

A combination of two features, which is useful when the relationship between two features is important.

A

Feature crosses

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13
Q

This is useful for reading in input features, where the inputs are too big to read into memory, so instead a worker loads the inputs into a queue and another operation pulls it off the queue for processing

A

Queues

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14
Q

A statistical way of comparing two (or more) techniques —the “A” and the “B”—typically an incumbent against a new rival.

A

A/B Testing

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15
Q

aims to determine not only which technique performs better but also to understand whether the difference is statistically significant

A

A/B Testing

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16
Q

The primary algorithm for performing gradient descent on neural networks

A

Backpropagation

17
Q

A method to train an ensemble where each constituent model trains on a random subset of training examples sampled with replacement.

A

Bagging

18
Q

short for bootstrap aggregating.

A

bagging

19
Q

A machine learning technique that iteratively combines a set of simple and not very accurate classifiers (referred to as “weak” classifiers) into a classifier with high accuracy (a “strong” classifier) by upweighting the examples that the model is currently misclassifying.

A

Boosting

20
Q

t’s first version was released in

A

1991

21
Q

It was written as the successor of programming language named

A

ABC

22
Q

The name Python was picked by Guido van Rossum from a TV show named

A

Monty Python’s Flying Circus.

23
Q

open source programming language which means that we can freely download it and use it to develop programs.

A

Python