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  • Arduino
  • Machine Learning & AI
  • Robotic Process Automation
  • Internet of thing
  • Rubic cube solving
  • Electrical Engineering
  • Content  Creating

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Pcb Fault Detection(Deep Learning Technique)

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  Hello,  that's how I applied my deep Learning skills to my electronics industry  application Technical except After iterating through many models we find this model to be giving good accuracy and least loss. we used  #yolo  v5 with 4000 epoch. here us the latest update to the dataset. I have gathered data related to pcb fault detection. I have gathered a huge amount of image data. and I have open sourced it via-Kaggle. feel free to explore it.
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environment creation on python

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  without conda : D:\Anney\environment>python -m venv magic_venv D:\Anney\environment>.\magic_venv\Scripts\activate (magic_venv) D:\Anney\environment> environment  conda: $ conda create --name [Virtual Environment Name] python=[Version you want to install] Example, $ conda create --name sample_venv python= 3.8  
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Project 2: pdf extractor using python

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let us prepare a project of few codes to extract the whole pdf    import pip install PyPDF2 code: ............................................................................................................................................. from PyPDF2 import PdfFileReader #read a pdf file ie. by rb mode file=open("Handbook.pdf",'rb') #reader ia s variable use to read file  reader=PdfFileReader(file) #lets get the info of the pdf document print("document info:",reader.getDocumentInfo()) print() #getNumPages() this comand can get you page numbers of pdf print("number pf pages are:",reader.getNumPages()) #lets take variable "pages" to take comand over get number of pages pages=reader.getNumPages() for i in range(0,pages):     print("page number=",i+1)     pageObj = reader.getPage(i)     print(pageObj.extractText()) print() print(reader.getDocumentInfo().creator) file.close() ............................................................
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