Package: witcher
witcherWitcher is an automated, driverless tool to build an error-free machine learning application.Witcher is an automated AI application designed to speed up the data processing phases.
The current witcher has :Recommender:will provide you with a comprehensive product recommendation using product popularity, product similarity and user similarity models.StockMarket :Will read the stock information from Yahoo API and analysis the Stock prices using ARIMA Time seriesFileChooser :Automated FileChooser function, Filechooser will read your data regardless it format and will provides you a Datafram. Currently witcher can read csv,xls,xlsx,sas,and images automaticalyImageToCartoon :A fun project will read your images and do some processing such as image blurred, edges extraction, image to cartoon,...Magical data processing, predictive, and deep learning models will be joining witchers functions very soon :)I hope you will enjoy using the witcher libraryThank you.Babak.EA
Founder and CEO: AI Forest IncHow to run :using Jupyter notbookimport wirtcherfrom witcher import Recommenderfrom witcher import StockMarketfrom witcher import FileChooserfrom witcher import ImageToCartoonfrom witcher import FileChooserFileChooser.Filechooser ==>
	
    will read the file and will returen the filename, filepath, and dataframe for
    CSV, XLS,XLSX, SAS, and Images
	

    Reprort=witcher.FileChooser.filechoose()
	
    Report
	

    report.files == > file path
	
    report.df ==> dataframe
	

from witcher import FileChooser, ImageToCartoon

    img=FileChooser.Filechooser()
	
    img
	

    image=img.df or
	
    image=ImageToCartoon.Img_Reader(img.files[0]) # read image and return numpy vector
	

    ImageToCartoon.ImageShow(image) ### Show the image
	
    Image_D=IMG_D=ImageToCartoon.Decolorization(image)
	
    Blurred=Blurred(image)
	
    edges=ImageToCartoon.Edgedetection(image)
	
    Bluured=ImageToCartoon.Blurred(image)
	
    Cartoon=Cartoon(bluured=Blurred,mask=edges)
	
    or
	
    Cartoon=Cartoon(bluured=Blurred,decolor=Image_D,mask=edges)
	


from witcher import StockMarket

    select your stock and starting date to end date
	
    df=StockMarket.Stock_Reader(stock=["AC.TO"],Period="1D",Start_date="2010-01-01",End_date="Today")
	
    df=StockMarket.Dataset_Spliter(df,col="Close",split=.1,Forecasting=True)
	
    select the column you want to analysis and pass it to the finction 


from witcher import Recommender

    submit your user products and run the recommender system
	
    Model_generator=Recommender.Model_Generator(User Product dataframe,User Satisfaction DataFrame,User Informatiin  dataframe ,knn_neighbors=number of the neighbors) 
	*** Witcher Recommender system work based on 3 different recommender systems, SVD, PCA, and KNN with a total accuracy of 80-85%
									

    df=StockMarket.Dataset_Spliter(df,col="Close",split=.1,Forecasting=True)
	Get Recommendation : 
	products=Recommender.Product_Recommender("User ID")
	Recommender.pprint.pprint(products.report)
	
    Recommendation for a new user: 
	products=Recommender.Product_Recommender("User Name",NEW_USER="True",USER_feature=[list of the selected producte by user]+[User incom]+[User satisfaction level] ( new user is 0))
	Recommender.pprint.pprint(products.report)How To Installpip install witchersource code : githubhttps://github.com/BabakEA/witcherYouTube:https://www.youtube.com/channel/UCBqqRv8vWV3NZFF2tQV4e-w