I find an data of amazon food reviews on kaggle …

Data was in raw format ,contains HTML tag and other unnecessary things,first we clean data using functions….

Then,done EDA to visualize the spread of class,as it is two class classification problem….Positive review and Negative review….

Then ,step by step we perform an various algorithm namely KNN,Naive Bayes,Logistic Regression,Decision Tree,GBDT,Random Forest,SVM etc..

find an best model by observing accuracy…

The GitHub link for the amazon Fine Food Reviews Sentiment Analysis is:


Blog By:

Akshay Bhor: Deep learning Engineer

an Data Scientist

This project is under development ,as I am facing some issues,but i am uploading whatever i done till now…

The vehicle number plate detection consists of 2 major parts…

  1. Detect vehicle number plate using pretrained model like yolo v3..
  2. Convert number on plate to digits using OCR and store it to database

The input image to the model is:

Akshay Bhor ..an Data Scientist

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