SHAURYA AGARWAL
All my technology and research in one place
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About
Open Source Initiatives
Data Munging Using X
Data Engineering Workshops with Spark (PySpark), Pandas, Dask, Ray etc - some of the most popular libraries in the field. Supports Google Colab, click on the 
badge next to each notebook’s link.
Notebooks on Statistics and Machine Learning
These serve as practical notes and references on common machine learning algorithms with an introduction to Pandas and Numpy.
Vogon Poetry
concepts like zero-copy-columnar-layout-distributed-vectorized etc. that sound like Vogon Poetry to data engineering teams trying to modernize their game…
The Data Engineering Rocket Ship
Long-form posts on data engineering and technology in collaboration with my team
CoolRE
Pronounced “cooler” provides 3 approaches to building a regular expressions engine - a toy overview, a backtracking based implementation and a finite-automata based approach.
Kandinsky
Discover key colours in a painting or photograph using K-Means clustering. Also provides the proportions of the colours. Some results (more in the repo):
Barnsley Fern Fractal
Phyllotaxis and L-systems example
Certifications
- Deeplearning.ai + Coursera - scored 100% across the board.
Trainings Archive / Older Material
- Topics in JavaScript, using Jupyter Notebooks
- Building x.509 certificates for MongoDB - was written originally to be used with MongoDB, may be outdated, see latest Mongo documentation. Still a good step-by-step on how to build a certificate.
- DC/OS Training - no longer current, it’s better to reference the DC/OS documentation.