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Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

Python 8.15% Jupyter Notebook 91.85%
data-science feature-engineering feature-selection python

amazing-feature-engineering's Introduction

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  • ๐Ÿ‘‹ Hi, Iโ€™m @shivpal
  • ๐Ÿ‘€ Extensive Working experience as a | Data Scientist | Machine Learning Engineer |
  • ๐ŸŒฑ Iโ€™m Working on Data Science | Machine Learning | Natural Language Processing | Deep Learning | Generative AI fields.
  • ๐ŸŒฑ Iโ€™m currently learning Natural Lannguage Processing (NLP) | Deep Learning | MLops/AIops | Generative AI
  • ๐Ÿ’ž๏ธ Iโ€™m looking to collaborate on providing & impoving solutions and advancements in technologies.
  • ๐Ÿ“ซ Reach me at [email protected]

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Languages:

c cplusplus java python

Data Scraping:

bs selenium

Databases:

sqlite mysql mongodb cassandra

ML/DL:

numpy pandas matplotlib seaborn scikit_learn pyspark nltk tensorflow pytorch tensorflow

Frameworks:

flask django streamlit

Clouds:

aws azure gcp heroku

Big Data:

hadoop hive

Version Control Tool:

git git

API Testing:

postman

Softwares:

anaconda

Web Development:

html5 css3 php

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ashishpatel26 avatar yimeng-zhang avatar

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