Hello, my name is
Deepakshi Mahajan
And I'm a Softw|
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About me

I'm Deepakshi and I'm a Machi|

Experienced Deep Learning and Machine Learning Engineer with demonstrated experience in working on predictive modelling, classification, object detection, computer vision, Deep Learning, and Machine Learning. I have studied and implemented real time projects in Computer Vision and NLP areas, namely Sentiment Analysis, Summary Generator, and Auto-corrector. Currently, Working on Face Masking and Virtual Makeup Tryon.

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My Experiences

GeeksforGeeks

● Building Scripts for Scraping, Extracting and Analyzing the Data.
● Worked on Youtube Channel Analysis
● Reviewed more than 120 articles related to Python and Machine Learning.

CloudTara

● Build OCRGraphReader using Amazon Rekognition and Pytesseract.
● Data Annotation on Bars
● Used LayoutLM transformer
● Created and Tested APIs using FLASK and POSTMAN.

AlgoAnalytics

● Demographic analysis of area.
● Predicted expected number of voters.
● Performed outlier detection, web scraping.
● Predicted Active Group on polling day.

Cureya

● Built ML models, learned new algorithms.
● Worked on pneumonia prediction by X-Ray images of patients' lungs.
● Used Ensembled Learning and trained model upto 96% accuracy.

My skills

My creative skills & experiences.

Experienced Deep Learning and Machine Learning Engineer with demonstrated experience in working on predictive modelling, classification, object detection, computer vision, Deep Learning, and Machine Learning. I have studied and implemented real time projects in Computer Vision and NLP areas, namely Sentiment Analysis, Summary Generator, and Auto-corrector. Currently, Working on Face Masking and Virtual Makeup

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Machine Learning 90%
Neural Networks 70%
HTML/CSS/Bootstrap5 80%
Flask 70%
Python 80%

My projects

Diabetes prediction

It is a ML model which uses different python libraries such as Numpy, Pandas, Scikit-Learn, Matplotlib,etc. to predict wheater the patient is diabetic or not. To implement all the codes I used Google colab and got the dataset from kaggle

I used different ML classifiers models to predict the accurate results. Also used ensembles models for better results.

Auto Summarizer

It is an NLP based project. It summarixes the text/ desctiption/ paragraphs by using techniques such as stop-words removal, lemmatization, tokenization, Vectorization, etc. I have also created the FLASK app with a very basic UI where user can add any description adn the model will predict the best suitable summary of it.

Taste of Slice

It is a Food Blog. It is static web application. It has a lot Indian and Italian reciepes to help different kinds of users to get reciepes and prepare food according to their taste and style.

I used HTML, CSS, Bootstrap5 for the frontend part of the website. I prepared this project on Visual Studio Code. I took help from google and wikipedia.

My Cars Webapp

It is a web application where user can login or register and view different car options before purchasing the real one. This app also have features of service booking, vehicles registeration , car price predcition

I used ML to predict the car price, PostgreSQL for storing database ,Django for backend and HTML , CSS and Bootstrap5 for frontend.

Diabetes prediction

It is a ML model which uses different python libraries such as Numpy, Pandas, Scikit-Learn, Matplotlib,etc. to predict wheater the patient is diabetic or not. To implement all the codes I used Google colab and got the dataset from kaggle

I used different ML classifiers models to predict the accurate results. Also used ensembles models for better results.

Auto Summarizer

It is an NLP based project. It summarixes the text/ desctiption/ paragraphs by using techniques such as stop-words removal, lemmatization, tokenization, Vectorization, etc. I have also created the FLASK app with a very basic UI where user can add any description adn the model will predict the best suitable summary of it.

Taste of Slice

It is a Food Blog. It is static web application. It has a lot Indian and Italian reciepes to help different kinds of users to get reciepes and prepare food according to their taste and style.

I used HTML, CSS, Bootstrap5 for the frontend part of the website. I prepared this project on Visual Studio Code. I took help from google and wikipedia.

My Cars Webapp

It is a web application where user can login or register and view different car options before purchasing the real one. This app also have features of service booking, vehicles registeration , car price predcition

I used ML to predict the car price, PostgreSQL for storing database ,Django for backend and HTML , CSS and Bootstrap5 for frontend.

Diabetes prediction

It is a ML model which uses different python libraries such as Numpy, Pandas, Scikit-Learn, Matplotlib,etc. to predict wheater the patient is diabetic or not. To implement all the codes I used Google colab and got the dataset from kaggle

I used different ML classifiers models to predict the accurate results. Also used ensembles models for better results.

Auto Summarizer

It is an NLP based project. It summarixes the text/ desctiption/ paragraphs by using techniques such as stop-words removal, lemmatization, tokenization, Vectorization, etc. I have also created the FLASK app with a very basic UI where user can add any description adn the model will predict the best suitable summary of it.

Contact me

Get in Touch
Name
Deepakshi Mahajan
Address
Delhi, India
Email
mahajandeepakshi03@gmail.com
Linkedin
deepakshi-mahajan
Github
mahajandeepakshi03
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