problem definition
data extraction
data preparation - data cleaning
data preparation - data transformation
data exploration and visualization
predictive modeling
model validation/test
deploy - interpretation of results
deploy - deployment of solution
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python was built upon what languge
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ABC
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summarization
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is a process by which data are reduced to interpretation without sacrificing important information
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pandas
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is the core of data analysis in python
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data visulization
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best tool to highlight possible patterns
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Travis Oliphant
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NumPy library 2006
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Data
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are the events recorded in the world
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numerical data
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are values or observations that come from measurments
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data analytics
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the process of extracting information from raw data
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python objectives
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interpreted
portable
object-oriented
interactive
interfaced
open source
east to understand and use
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Guido Von Rossum, 1991
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the python language was created by
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ordinal
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variable instead has a predetermined order
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classification models
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if the result obtained by the model is type categorical
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numpy
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is the foundation library for scientific computing in python since it provides data sructures and high-performing functions that the basic package of python cannot
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in documentation supplied by the analyst, each of the four topic will be discussed
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analysis results
decision deployment
risk analysis
measuring the business impact
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machine learning
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is a discipline that uses a whole series of procedures and algorithms that analyze the data in order to recognize patterns, cluster, or trends and then extracts useful information for data analysis in an automated way
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discrete
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values can be counted and are distinct and separated from each other
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Numeric
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Jim Hugunin, 1995
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2008
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python 3.0 made its first appearance in 2008
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qualitative analysis
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deals with values that are expressed through descriptions in natural language
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data exploration
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consists of a preliminary examination of the data, which is important for understanding the type of information that has been collected and what it means
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categorical data
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are values or observations that can be divided into groups or categories
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continuous
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values are produced by measurements or observations that assume any value within a defined range
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data preparation
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is concerned with obtaining, cleaning, normalizing, and transforming data into an optimized dataset, that is, in a prepared format that normally tabular and is suitable for the methods of analysis that have been scheduled during the design phase
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quantitative analysis
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when the analyzed data have a strictly numerical or categorical structure
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regression models
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is the results obtained by the model type is numeric
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interpreter
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runs the code
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DataFrame
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a two-dimmensional tabular structure with row and column labels
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clustering
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is a method of data anlysis that is used to find groups united by common attributes (grouping)
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aim of data analysis
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is not the model, but the quality of its predictive power
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nominal
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variable has no intrinsic order that is identified in its category
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predictive modeling
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is a process used in data analysis to create or choose a suitable statistical model to predict the probabiliy of a result
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clustering models
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is the result obtained by the model is type descriptive
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to get input
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myname = input("What is your name?)
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machine learning
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one of the most advanced tool that falls in the data analysis camp
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negative indices
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if you are using _____________ __________, this means you are considering the last item in the list and gradually moving to the first
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object-oriented
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allows you to specify classes of objects and implement their inheritance
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tokenization
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each time you press the enter key, the interpreter begins to scan the code token by token