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  • OCBC Bank
  • Singapore

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princyiakov/README.md
  • 👋 Hi, I’m Princy Pappachan Iakov
  • 👀 I’m interested in Data Science, Deep Learning, Computer Vision, Natural Language Processing and all things which can bring a positive influence in this world and make life better for every individual !
  • 📫 You can reach me at [email protected]

Let me give you a quick tour if you are interested in my projects !

🌟 My NLP contributions for Giskard : Sentiment Analysis for twitter Data

  • You can find the notebook for the project here
  • LANGUAGE : Python
  • LIBRARIES IMPLEMENTED : transformers, tweepy, datasets, torch and giskard
  • MODELS EXPLORED : DistillBERT

🌟 Chronic Kidney Disease Progression

  • You can find the project here
  • LANGUAGE : Python
  • LIBRARIES IMPLEMENTED : lifelines, pandas, seaborn, plotly, matplotlib
  • MODELS EXPLORED : KaplanMeierFitter, KNN, Random Forest, Logistic Regression

🌟 Fraud Detection in Blockchain transactions

  • You can find the notebook for the project here
  • LANGUAGE : Python
  • LIBRARIES IMPLEMENTED : pandas, seaborn, plotly, matplotlib
  • MODELS EXPLORED : Random Forest, XGBoost, Logistic Regression

🌟 Personal Drone Programming and Computer Vision : Facial Recognition to help recognise registered missing people and self flying drone

missing_person

princy_drone

  • A project close to my heart to help recognise missing children or adults who are reigtered
  • You can find the code here
  • LANGUAGE : Python
  • DATABASE : PostgreSQL
  • PYTORCH implementation
  • Facial Recognition using FaceNet (MTCNN and InceptionResnetV1)
  • Registration of missing people using a simple front end Flask Implementation

🌟 My NLP contributions for Giskard : Email Classification

  • You can find the notebook for the project here
  • LANGUAGE : Python
  • LIBRARIES IMPLEMENTED : torch, nltk, transformers, sklearn and giskard
  • MODELS EXPLORED : Hugging Face BERT, Logistic Regression

🌟 My NLP contributions for Giskard : Text Classificcation using Tensorflow

  • You can find the notebook for the project here
  • LANGUAGE : Python
  • LIBRARIES IMPLEMENTED : tensorflow, pandas and giskard
  • MODELS EXPLORED : simple binary classifier

🌟 My contributions for Giskard : House Pricing Regression

  • You can find the notebook for the project here
  • LANGUAGE : Python
  • LIBRARIES IMPLEMENTED : sklearn, pandas, numpy and giskard
  • MODELS EXPLORED : Random Forest, Catboost

🌟 Personal Project - Classification for Tabular Data Project : Credit Card Default project

  • You can find the notebook for the project here
  • LANGUAGE : Python
  • LIBRARIES IMPLEMENTED : sklearn, seaborn, matplotlib, plotly, imblearn
  • MODELS EXPLORED : XGBoost, Random Forest, Decision Tree, KNN
  • I have performed EDA and visualization using Matlabplot lib and Plotly
  • Feature Engineering and Feature Selection
  • Explored various Sampling techniques
  • Will be implementing a front end for the application and creating an image on docker

🌟 First Docker Implementation : Video Process

  • In my first attempt at docker implementation, I reinitiated an existing code of correcting a corrrupted video and packaged into a python library and created a docker image
  • You can find the code here
  • LANGUAGE : Python

🌟 Amazon Web Services(AWS) : Jump Box implementation

  • You can find the implementation here

Pinned Loading

  1. credit-card-default credit-card-default Public

    Jupyter Notebook

  2. videoprocess videoprocess Public

    Python

  3. Drone_Face_Recognition Drone_Face_Recognition Public

    Python

  4. Drone_Face_Tracking Drone_Face_Tracking Public

    Python

  5. Face_Recognition Face_Recognition Public

    Python

  6. Covid_Detection_From_XRAY Covid_Detection_From_XRAY Public

    Jupyter Notebook 1