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amitesh-pandey/README.md

Hi there 👋

I'm Amitesh Pandey ✌️

Being an enthusiastic Post Graduate Engineer, I have been working in the Tech industries since 3+ years with different technology and domains. Thus, I believe in Learning, by adapting a new technology using ELE concept:
E -> Exploring new technology,
L -> Learning it conceptually ,
E -> Executing it instantly.

💖 Currently working as a Researh Data Scientist, in the Cyber Security domain, working on the XDR Product (Extended Detection & Response) dealing with the implementation of Multiple Unified Model Usecases(UEBA, Web & Network) with respect to the severity level, further performing a white box testing of those alerts for the Quality analysis of the product. Also Involved in the Kafka as a data forwarder, pushing the Alerts generated from the ML to MongoDB.

🌈 I am skilled in some of domain mentioned below:

  1. Python Libraries: Pandas, Sklearn, Matplotlib, Seaborn, Tensorflow, Keras, Beautiful Soup, Spacy
  2. Domain Knowledge: Machine Learning || Deep Learning || Natural Language Processing
  3. Programming IDE: Jupiter Notebook || Pycharm || Spyder
  4. Operating System: Windows || Linux (Ubuntu)
  5. Deployment platform: Flask || Postman || Heroku
  6. Database: MySQL || MongoDB
  7. Additional: GitHub/GitLab || Software Defined Radio

📫 How to reach me:

📍 Email : pamitesh123@gmail.com

📍 Linkedin : https://www.linkedin.com/in/amiteshpandey-1992/

Popular repositories

  1. Practical_Approach_to_SDR Practical_Approach_to_SDR Public

    As the title suggests,you get to understand the the concepts of Software Defined Radio and hardware/software that help in wireless system design. After extensive survey it was found that adopting o…

    Python 7 4

  2. BostonHousePrediction_ModelDeplyoment-Heroku BostonHousePrediction_ModelDeplyoment-Heroku Public

    Creating a model to predict the pricing of the Boston house and create its framework using Flask and deploy it using Heroku

    Jupyter Notebook 4

  3. StockMarketPrediction-Unsupervised-KMean-Deployment-Heroku StockMarketPrediction-Unsupervised-KMean-Deployment-Heroku Public

    The model is created for predicting the stock market price prediction based on the group using Kmean Clustering Algorithm and further deploying it using flask and Heroku platform

    Jupyter Notebook 3

  4. Classification_Based_Supervised_Machine_Learning_Algorithm Classification_Based_Supervised_Machine_Learning_Algorithm Public

    Creating a working machine learning model which predicts whether the following customer will purchase the Brand new SUV car or not and also identifying which classification algorithm best fits the …

    Jupyter Notebook 2

  5. Creating_Artificial_Neural_Network Creating_Artificial_Neural_Network Public

    Creating a Working Model using Artificial Neural Network to predict whether the following customer will leave the Bank or will continue being the member of Bank

    Jupyter Notebook 2

  6. Sentimental-Analysis-on-Customers-feedback Sentimental-Analysis-on-Customers-feedback Public

    Applying the Sentimental Model Analysis on the feedback of People whether it is positive or negative based on the service provided using Machine Learning and Natural Language Processing Concepts

    Jupyter Notebook 2