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Working on ML/Deep Learning Projects
:octocat:
Working on ML/Deep Learning Projects

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ashish-kamboj/README.md

Hi 👋, I'm Ashish Kamboj

A passionate about developing and deploying end-to-end Machine Learning applications

ashish-kamboj

ashish-kamboj

  • 🌱 I’m currently learning Deep Learning, NLP, Computer Vision
  • 👯 I’m looking to collaborate on Open source projects in python
  • 👨‍💻 All of my projects are available at Portfolio
  • 💬 Ask me about Python, ML Model deployment, Automation
  • 📫 How to reach me Email: [email protected]
  • 📄 Know about my experiences Portfolio
  • ⚡ Fun fact I am Fitness Freak

Connect with me:

ashish-kamboj ashukamboj

Skills:

Programming Languages

c java python

Frontend Development

bootstrap css3 html5 tailwind flask

Big Data

hadoop hive

Databases

mongodb mssql mysql oracle postgresql elasticsearch

Data Visualization

kibana grafana

AI/ML

aws scikit_learn pandas Apache Airflow

DevOps

docker git kubernetes jenkins postman

ashish-kamboj

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  1. Market-Mix-Modeling Market-Mix-Modeling Public

    Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales

    R 40 28

  2. Data-Science Data-Science Public

    EDA and Machine Learning Models in R and Python (Regression, Classification, Clustering, SVM, Decision Tree, Random Forest, Time-Series Analysis, Recommender System, XGBoost)

    Jupyter Notebook 16 8

  3. mlops mlops Public

    Repository contains the detail about ML model deployment and building end-to-end ML pipeline for production

    Python 2 2

  4. NLP NLP Public

    Text data analysis, Name-Entity Recognition and Topic Modeling for automating and building ML models

    Jupyter Notebook 4 4

  5. ml-dl-techniques ml-dl-techniques Public

    Code snippet for different machine learning and deep learning techniques for model building, feature engineering, missing value imputation, EDA, and data reading/pulling/extraction/cleaning.

    Jupyter Notebook

  6. learning-material learning-material Public

    Contains questions, ebooks, and courses related to Data Science, Machine Learning, R, Python, and Spark.

    Python 2 1