Intro Flashcards

(33 cards)

1
Q

What is normal programming vs machine learning?

A

Normal programming is putting rules to get input to output

Machine learning is giving the input and output and generating the rules

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2
Q

What are convolutional networks best for?

A

Computer vision and identifying images.

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3
Q

What is an autoencoder?

A

network architecture used for image compression and denoising

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4
Q

What is transfer learning?

A

Used to classify things a set has never seen before?

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5
Q

What are recurrent neural networks best for?

A

Data that forms sequences like text, music, and time series data.

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6
Q

Generative adversarial networks are best for

A

Image generation

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7
Q

RNN SF

A

Recurrent Neural Network

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8
Q

GAN SF

A

Generative Neural Networks

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9
Q

What is Sci-Kit learn

A

Machine Learning library for Python

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10
Q

Percetrons are

A

The simplest forms of a neural network

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11
Q

Gradient descent is

A

A process by which Machine Learning algorithms learn to improve themselves based on the accuracy of their predictions.

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12
Q

Backpropagation is

A

The process by which neural networks learn how to improve individual parameters

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13
Q

Numpy is

A

An extremely popular library for scientific computing in python

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14
Q

Tensorflow is

A

One of the most popular python libraries for creating neural networks. It is maintained by Google.

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15
Q

Command to create a new conda environment

A

conda create -n name_of_env python=3

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16
Q

To enter a conda environment

A

source activate name_of environment

17
Q

To see a list of my conda environments

A

conda info –envs

18
Q

To see a list of the packages installed in a conda

19
Q

To add a version to conda use (numpy as an example)

A

conda install numpy=1.10

20
Q

To update all conda packages

A

conda update –all

21
Q

Which of these commands would you use to install the packages numpy and pandas with conda?

A

conda install pandas
or
conda install numpy pandas
Pandas includes numpy

22
Q

To export conda packages

A

conda env export > environment.yaml

23
Q

How did Jupyter Notebooks start?

A

grew out of the IPython project started by Fernando Perez

24
Q

What are magic keywords?

A

special commands you can run in cells that let you control the notebook itself or perform system calls such as changing directories

25
JN % is
Line magics
26
JN %% is for
cell magics
27
To test for how fast something completes in JN run
%timeit function_name()
28
To test for how long your cell takes to run in RN
%%timeit on the top of the cell
29
To render figures directly in the JN notebook, you should use the inline backend with the command
%matplotlib inline
30
To render higher quality images in JN
%config InlineBackend.figure_format = 'retina'
31
To turn on the interactive Python debugger in JN use
%pdb
32
To convert a JN to html
jupyter nbconvert --to html notebook.ipynb
33
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