PACKT_PUBLISHING_LEARNING_PATH_PYTHON_EFFECTIVE_DATA_ANALYSIS_USING_PYTHON_TUTORIAL-OXBRiDGE

Section
Appz
Group
OXBRiDGE
Size
2,58 GB
Files
58
Date
2017-05-12

NFO

                                           
░ ░▒▒▒▓▓█████▌░░ University of OXford & University of camBRiDGE ░░▐████▓▓▒▒▒░ ░
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  ...is a collective term for characteristics that the two institutions share.


     ·-- PUBLISHED -----·> Packt Publishing                                   
     ·-- LECTURESHIP ---·> Learning Path: Python: Effective Data Analysis     
                           Using Python                                       
                                                                              

     ·-- LECTURE DATE --·> 05-2017           
                           04-2017 {Published}

     ·-- LEVEL ---------·> [ ] Starting {Beginner|Newcomer}
                           [■] Progressing {Intermediate|Advanced}

     ·-- PERIOD in HRS--·> 11+                                 
     ·-- SCALE ---------·> 56x50mb                                           

     ·-- LECTURE LINK --·> https://goo.gl/ql58fG                     
                                                                     
                                                             
 
     
     This path navigates across the following products                       
     (in sequential order):                                                  
                                                                             
     Learning Python Data Analysis (5h 55m)                                  
     Getting Started with Python Web Scraping (1h 36m)                       
     Python Data Visualization Solutions (3h 27m)                            
                                                                             
     Data analysis as we know it is the process taking the source data,      
     refining it to get useful information, and then making useful           
     predictions from it.                                                    
                                                                             
     Python features numerous numerical and mathematical toolkits such as:   
     Numpy, Scipy, Scikit learn and SciKit, all used for data analysis and   
     machine learning. With the aid of all of these, Python has become the   
     language of choice for data scientists for data analysis, visualization,
     and machine learning.                                                   
                                                                             
     We will have a general look at data analysis and then then discuss the  
     Web scraping tools and techniques in detail. We will show a rich        
     collection of recipes that will come in handy when you are scraping a   
     website using Python, addressing your usual and unusual problems while  
     scraping websites by diving deep into the capabilities of PythonÆs web  
     scraping tools such as Selenium, BeautifulSoup, and urllib2.            
                                                                             
     We will then discuss the visualization best practices. Effective        
     visualization helps you get better insights from your data, and help you
     make better and more informed business decisions.                       
                                                                             
     After completing this Learning Path, you will be well-equipped to       
     extract data even from dynamic and complex websites by using Python web 
     scraping tools, and get a better understanding of the data visualization
     concepts, how to apply them, and how you can overcome any challenge     
     while implementing them.                                                
     

Files

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o_pplppedaupt.sfv1,53 KB
oxbridge.nfo4,19 KB