FA5 + M5 - Sheet1 Flashcards by Ralph Gamboa

Which of the following libraries are used for mathematical and statistical operations on multi-dimensional arrays and matrices in Python?

Group of answer choices

Matplotlib

NumPy

Pandas

NumPy

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Which of the following libraries are used for data visualization in Python?

Group of answer choices

NumPy

Matplotlib

SciPy

Matplotlib

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Which of the following libraries are used for deep learning in Python?

Group of answer choices

TensorFlow

Scikit-learn

Keras

TensorFlow

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Which of the following libraries are used for natural language processing in Python?

Group of answer choices

NLTK

Scrapy

Scikit-learn

NLTK

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Which of the following libraries are used for creating spiders bots that scan website pages and collect structured data in Python?

Group of answer choices

Scrapy

Pandas

SciPy

Scrapy

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Which of the following libraries are used for object identification, speech recognition, and more in Python?

Group of answer choices

PyTorch

Keras

Dist-keras

Tensorflow dapat pero Pytorch ung tama sa canvas

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Which of the following libraries are used for reading data, selecting and filtering in data, and data manipulations in Python? There are two correct answer in the options, just choose one.

Group of answer choices

PyTorch

Pandas

NumPy

SciPy

Pandas
NumPy

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Which of the following libraries are used for creating interactive and scalable visualizations in a browser using JavaScript widgets in Python? There are two correct ansers from the choices, just select one.

Group of answer choices

SciPy

Bokeh

NumPy

Bokeh

Plotly

NumPy

SciPy

Bokeh
Bokeh

Plotly
Plotly

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Which Python libraries are built on NumPy? There are two correct ansers from the choices, just select one.

Group of answer choices

Pandas

Seaborn

Scikit-Learn

Matplotlib

Pandas
Scikit-Learn

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Which Python library provides machine learning algorithms?

Group of answer choices

Pandas

Scikit-Learn

NumPy

Matplotlib

Scikit-Learn

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Data Wrangling:

SciPy
NumPy
pandas

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Statistic

StatsModels

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NLP

Natural Language Toolkit
SpaCy
gensim

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Machine Learning

scikitlearn
xgboost
lightgbm
catboost
eli5

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Deep Learning

TensorFlow
Pytorch
Keras

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Distributed Deep Learning

dist-keras
elephas
spark-deep-learning

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Visualization

matplotlib
Bokeh
plotly
Seaborn
pydot

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it is intended for processing large multidimensional arrays and matrices, and an extensive collection of high-level mathematical functions and implemented methods makes it possible to perform various operations with these objects

NumPy (numpy.org)

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it is based on NumPy and therefore extends its capabilities. SciPy main data structure is again a multidimensional array, implemented by Numpy.

SciPy (scipy.org/scipylib)

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The package contains tools that help with solving linear algebra, probability theory, integral calculus and many more tasks

SciPy

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provides high-level data structure and a vast variety of tools for analysis. The great feature of this package is the ability to translate rather complex operations with data into one or two commands.

Pandas (pandas.pydata.org)

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contains many built-in methods for grouping, filtering, and combining data, as well as the time-series functionality

Pandas

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is a low-level library for creating two-dimensional diagrams and graphs.

Matplotlib (matplotlib.org)

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With iths help, you can build diverse charts, from histograms and scatterplots to non-Cartesian coordinates graphs.

Matplotlib (matplotlib.org)

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Moreover, many popular plotting libraries are designed to work in conjunction with ____

matplotlib

is essentially a higher-level API based on the matplot library.

Seaborn (seaborn.pydata.org)

It contains more suitable default settings for processing charts.

Seaborn

Also, there is a rich gallery of visualizations including some complex types like time series, jointplots, and violin diagrams

Seaborn

is a popular library that allows you to build sophisticated graphics easily.

Plotly (plot.ly/python/)

The package is adapted to work in interactive web applications.

Plotly

Among its remarkable visualizations are contour graphics, ternary plots, and 3D charts

Plotly

The ____library creates interactive and scalable visualizations in a browser using JavaScript widgets.

Bokeh (bokeh.pydata.org/en/latest/)

The library provides a versatile collection of graphs, styling possibilities, interaction abilities in the form of linking plots, adding widgets, and defining callbacks, and many more useful features.

Bokeh

is a popular framework for deep and machine learning, developed in Google Brain.

TensorFlow (tensorflow.org)

It provides abilities to work with artificial neural networks with multiple data sets.

TensorFlow

Among the most popular TensorFlow applications are _____ and more.

object identification, speech recognition,

is a large framework that allows you to perform tensor computations with GPU acceleration, create dynamic computational graphs and automatically calculate gradients.

PyTorch (pytorch.org)

Above this, ____ offers a rich API for solving applications related to neural networks

PyTorch

is a high-level library for working with neural networks, running on top of TensorFlow, Theano, and now as a result of the new releases.

Keras (keras.io)

It simplifies many specific tasks and greatly reduces the amount of monotonous code. However, it may not be suitable for some complicated things.

Keras (keras.io)

These packages allow you to train neural networks based on the Keras library directly with the help of Apache Spark

Dist-keras (joerihermans.com/work/distributed-keras/)

dist-keras and others are gaining popularity and developing rapidly, and it is very difficult to single out one of the libraries since they are all designed to ______

solve a common task.

This Python module based on NumPy and SciPy is one of the best libraries for working with data.

Scikit-learn (scikit-learn.org/stable)

It provides algorithms for many standard machine learning and data mining tasks such as clustering, regression, classification, dimensionality reduction, and model selection

Scikit-learn

is an extension module that makes several frequent item set mining implementations available as functions.

PyFim

In PyFim, Currently _______ are available as functions, although the interfaces do not offer all of the options of the command line progarm

apriori, eclat, fpgrowth, sam, relim, carpenter, ista, accretion and apriacc

Often the results of machine learning models predictions are not entirely clear, and this is the challenge that ___ library helps to deal with.

eli5

it is a package for visualization and debugging machine learning models and tracking the work of an algorithm step by step.

Eli5 (eli5.readthedocs.io/en/latest/)

It provides support for scikit-learn, XGBoost, LightGBM, lightning, and sklearn-crfsuite libraries and performs the different tasks for each of them

eli5

is a set of libraries, a whole platform for natural language processing.

NLTK (nltk.org)

With the help of ____, you can process and analyze text in a variety of ways, tokenize and tag it, extract information, etc.

NLTK

is also used for prototyping and building research systems

NLTK

is a Python library for robust semantic analysis, topic modeling and vector-space modeling, and is built upon Numpy and Scipy.

Gensim (radimrehurek.com/gensim)

Gensim provides an implementation of popular NLP algorithms, such as _____.

word2vec

Although gensim has its own models.wrappers.fasttext implementation, the ____ can also be used for efficient learning of word representations.

fasttext library

is a library used to create spiders bots that scan website pages and collect structured data.

Scrapy (scrapy.org)

In addition, Scrapy can extract data from the ___

API

The library happens to be very handy due to its extensibility and portability

Scrapy

Introduces for multi-dimensional arrays and matrices, as well as functions that allow to easily perform advanced mathematical and statistical operations on those objects

NumPy

Provides vectorization of mathematical operations on array and matrices which significantly improves the performance

NumPy

Many other python libraries are built on ____

NumPy

adds data structures and tools designed to work with table - like data (similar to Series and Data Frames in R)

Pandas

Provides tools and data manipulation: reshaping, sorting, slicing, aggregation etc.

Pandas

Allow handling missing data

Pandas

provides machine learning algorithms: classification, regression, clustering, and model validation

Scikit-Learn

Build on NumPy, SciPy, and matplotlib

Scikit-Learn

Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats

matplotlib

A set of functionalities similar to those of MATLAB

matplotlib

Line plots, scatter plots, bar charts, histograms, pie charts etc

matplotlib

Relatively low-level; some effort needed to create advanced visualization

matplotlib

based on matplotlib. Provides high level interface for drawing attractive statistical graphics

Seaborn

Seaborn is similar (in style) to the popular ___ library in R

ggplot2

Loading Python Libraries

import numpy as np import scipy as sp impor pandas as pd import matplotlib as mpl import seaborn as sns

Press ____ to execute jupyter cell

Shift+Enter

There are numerous commands to read other data formats:

pd.read.excel(‘myfile.xlsx’, sheet_name = ‘Sheet1’, index_col = None, na_values = [‘NA’]) pd.read_stata(‘myfile.dts’)

List first 5 records

df.head()

To view the first 10 records

pd.iloc[:10]

To view the last few records

df.tail(10)

The most general dtype. Will be assigned to your column if column has mixed type numbers and strings

object (string)

Numeric characters, 64 refers to the memory allocated to hold this character

Int64 (Int)

Numeric characters with decimals. If a column contains number and Nans, pandas will default to float64, in case your missing value has a decimal

Float64 (Float)

Values meant to hold time data. Look into these for time series experiments

Datetime64, timedelta[ns] (N/A)

Check a particular column type

df['salary'].dtype

Check types for all the columns

df.dtypes

list the types of the columns

dtypes

list the column names

columns

list the row labels and column names

axes

number of dimensions

ndim

number of elements

size

return a tuple representing the dimensionality

shape

numpy representation of the data

values

Unlike attributes, python methods have ___

parentheses.

All attributes and methods can be listed with a ____

dir() function

first/last n rows

head( [n] ), tail( [n] )

generate descriptive statistics (for numeric columns only)

describe()

return max/min values for all numeric columns

max(), min()

return mean/median values for all numeric columns

mean(), median()

standard deviation

std()

returns a random sample of the data frame

sample([n])

drop all the records with missing values

dropna()

Using “group by” method we can:

Split the data into groups based on some criteria Calculate statistics (or apply a function) to each group Similar to dplyr() function in R

group data using rank

df_rank = df.groupby(['rank'])

To subset the data we can apply ____

Boolean indexing.

To subset the data we can apply Boolean indexing. This indexing is commonly known as a ____

filter

Any ____ can be used to subset the data:

Boolean operator

There are a number of ways to subset the Data Frame:

one or more columns one or more rows a subset of rows and columns

Rows and columns can be selected by their position or label

Slicing

When selecting one column, it is possible to use single set of brackets, but the resulting object will be a ____(not a DataFrame):

Series

When we need to select more than one column and/or make the output to be a DataFrame, we should use ____

double brackets:

When summing the data, missing values will be treated as ___

zero

If all values are missing, the sum will be equal to____

NaN

methods ignore missing values but preserve them in the resulting arrays

cumsum() and cumprod()

Missing values in ___ method are excluded (just like in R)

GroupBy

Many descriptive statistics methods have ___ option to control if missing data should be excluded. This value is set to True by default (unlike R)

skipna

computing a summary statistic about each group, i.e. compute group sums or means compute group sizes/counts

Aggregation

Common aggregation functions:

min, max count, sum, prod mean, median, mode, mad std, var

are useful when multiple statistics are computed per column

agg()

Basic statistic (count, mean, std, min, quantiles, max)

describe()

Minimum and maximum values

min, max

Arithmetic average, median, and mode

mean, median, mode

Variance and standard deviation

var, std

Standard error of mean

sem

Sample skewness

skew

kurtosis

kurt

histogram

displot

estimate of central tendency for a numeric variable

barplot

similar to boxplot, also shows the probability density of the data

violinplot

Scatterplot

jointplot

regression plot

regplot

Pairplot

pairplot

Boxplot

boxplot

categorical scatterplot

swarmplot

general categorical plot

factorplot

both have a number of function for statistical analysis

statsmodel and scikit-learn

mostly used for regular analysis using R style formulas

statsmodel

is more tailored for Machine Learning

scikit-learn

statsmodels:

inear regressions ANOVA tests hypothesis testings many more

scikit-learn:

kmeans support vector machines random forests many more

FA5 + M5 - Sheet1 Flashcards

(138 cards)