on 26-Jan-2020 (Sun)

Flashcard 4872315211020

Tags
#DataScience
Question
In hypothesis testing, the proposed model is built on which dataset:
the training dataset.

status measured difficulty not learned 37% [default] 0

Flashcard 4872330415372

Tags
#DataScience #statistics
Question
Inferential analytics..

uses the probability theory to arrive at a conclusion.

Example:

Categorize height as “Tall,” “Medium,” and “Short”
Take a sample to study from the population.

z-test or t test?

status measured difficulty not learned 37% [default] 0

Flashcard 4872364494092

Tags
#DataScience
Question
Hypothesis Testing – Error Types

The null hypothesis corresponds to the position of the defendant: just as he is presumed to be innocent until proven guilty, so is the null hypothesis presumed to be true until the data provide convincing evidence against it.

Type I Error (α)
• Rejects the null hypothesis when it is true
• The probability of making Type I error is represented by α

(also known as a "false positive")

In terms of the courtroom example, a type I error corresponds to convicting an innocent defendant.

Type II Error (β)
• Fails to Reject the null hypothesis when it false
• The probability of making Type II error is represented by β

(also known as a "false negative" )

The alternative hypothesis corresponds to the position against the defendant.
In terms of the courtroom example, a type II error corresponds to acquitting a criminal.

status measured difficulty not learned 37% [default] 0

Flashcard 4872416136460

Tags
#python
Question

A tuple is:

1. ? dimensional
2. mutable/immutable
3. ordered/unordered sequence of items
4. single/mixed data types

A tuple is:

1. 1 dimensional
2. immutable
3. ordered
4. mixed data types

status measured difficulty not learned 37% [default] 0

Flashcard 4881236757772

Tags
#python
Question
What does the enumerate function do?

provides the index to the list, followed by the value.

example:

somelist = ['a','b','c']
for position, name in enumerate(somelist):
print position, name

will give:

0 a
1 b
2 c

status measured difficulty not learned 37% [default] 0

Flashcard 4881238592780

Tags
#python
Question
functions to sort
sorted, reversed

status measured difficulty not learned 37% [default] 0

Flashcard 4881240427788

Tags
#python
Question
What function is used to pair the data elements of lists. (Returns list of tuples.)
zip

status measured difficulty not learned 37% [default] 0

Flashcard 4881242262796

Tags
#python
Question
Pythons syntax for Exception Handling.

try:
except ValueError:

(check types of errors)

status measured difficulty not learned 37% [default] 0

Flashcard 4881244097804

Tags
#python
Question
Limitations of lists, vs numpy lists.
Cannot apply a mathematical operation over a normal list.

status measured difficulty not learned 37% [default] 0

Flashcard 4881245932812

Tags
#python
Question
what is ndarray.ndim used for?
It gives the number of axes (dimensions) of the array. It is also called the rank of the array.

status measured difficulty not learned 37% [default] 0

Flashcard 4881247767820

Tags
#python
Question
What is ndarray.shape

Returns a tuple of integers showing the size of the array in each dimension.

(4L,) -> 1 dimension array,4 items
(2L,4L) -> 2D array, 4 items each.

status measured difficulty not learned 37% [default] 0

Flashcard 4881249602828

Tags
#python
Question
ndarray.size ?
It gives the total number of elements in the array. It is equal to the product of the elements of the shape tuple.

status measured difficulty not learned 37% [default] 0

Flashcard 4881251437836

Tags
#python
Question
ndarray.dtype ?
Describes the type of the elements in the array.
sg S7 -> string, of longest length 7

status measured difficulty not learned 37% [default] 0

Flashcard 4881253272844

Tags
#python
Question
numpy logical condition syntax

np.logical_and(condition1,condition2)

np.logical_not(condition)

status measured difficulty not learned 37% [default] 0

Flashcard 4881255107852

Tags
#python
Question
numpy Accessing Array Elements.

np.array[0] eg first set

np.array[0][0]. eg first set, first element.

np.array[:,1:3] . slices all the rows, then columns 1:3 (1 to 2)

status measured difficulty not learned 37% [default] 0

Flashcard 4881256942860

Tags
#python
Question
Indexing with Boolean Arrays

filter = value>1

value(filter)

status measured difficulty not learned 37% [default] 0

Flashcard 4881258777868

Tags
#python
Question
python. view vs copy . Syntax and differences

array.view() . changes made to the new array will affect the original.

array.copy() . changes only made to the new array.

status measured difficulty not learned 37% [default] 0

Flashcard 4881260612876

Tags
#python
Question
Python shape manipulation functions
Flatten, Resize, Stack , Reshape, Split
Flatten: array.ravel()
Reshape: array.reshape(3,4) #3 rows, 4 columns
Resize: array.resize(2,6) #2 resizes again to 2rows, 6 columns
Split: np.hsplit(array,2) #splits array to 2
Stack: np.hstack((array1,array2,2))

status measured difficulty not learned 37% [default] 0

Flashcard 4881262447884

Tags
#python
Question
Linear Algebra functions. transpose, inverse, trace.

array=np.array([[1,2,3,4],[5,6,7,8]])

array.transpose()
np.linalg.inv(array) #eg 1/value
np.trace(array) #sum of diagonals left to right only

status measured difficulty not learned 37% [default] 0

Flashcard 4881264282892

Tags
#python
Question
A NumPy ndarray can hold single/multiple data type?
A NumPy ndarray can hold single data type = homogenous.

status measured difficulty not learned 37% [default] 0

Flashcard 4881298623756

Tags
#python
Question
Why Pandas ?
Easy data aggregation and transformation. Tools for reading/ writing data.
Fast and efficient data wrangling.
Intelligent and automated data alignment.
High performance merging and joining of data sets.
Functions for handling missing data.
Data standardization functions.

status measured difficulty not learned 37% [default] 0

Flashcard 4883816254732

Tags
#python
Question

create a panda series.

from which type of data?

import pandas as pd

someSeries = pd.Series(list/nd.array)
someSeries = pd.Series(5. , index['a','b','c'])
someSeries = pd.Series([1,2,3] , index['a','b','c']) #like a dictionary

status measured difficulty not learned 37% [default] 0

Annotation 4883820973324

 #anki #learning #spaced_repitition One day in the mid-1920s, a Moscow newspaper reporter named Solomon Shereshevsky entered the laboratory of the psychologist Alexander Luria. Shereshevsky's boss at the newspaper had noticed that Shereshevsky never needed to take any notes, but somehow still remembered all he was told, and had suggested he get his memory checked by an expert.

Augmenting Long-term Memory
emory Michael Nielsen | Y Combinator Research | July 2018 Related Resources Michael Nielsen on Twitter Michael Nielsen's project announcement mailing list cognitivemedium.com By Michael Nielsen <span>One day in the mid-1920s, a Moscow newspaper reporter named Solomon Shereshevsky entered the laboratory of the psychologist Alexander Luria. Shereshevsky's boss at the newspaper had noticed that Shereshevsky never needed to take any notes, but somehow still remembered all he was told, and had suggested he get his memory checked by an expert. Luria began testing Shereshevsky's memory. He began with simple tests, short strings of words and of numbers. Shereshevsky remembered these with ease, and so Luria gradually increased t

Flashcard 4884388515084

Question
MCB 150 Spring 2020