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About

I'm passionate about machine learning, big data, debugging, software craftsmanship, teaching, coaching, building engineering organizations that solve challenging problems effectively, helping others with their aspirations, and writing about the above.

My personal mission is to empower people around the globe to collaborate more effectively using software that provides great experiences.

Bio

https://elgeish.com

Computing with Data

Book Cover

A Guide Book to the Data Industry

  • Introduces programmers to data science concepts and practices through new apparatuses such as Python programming and data processing techniques
  • Explains prevalent programming languages and data processing systems that are commonly used to address engineering challenges
  • Explores new tools and libraries to use in big data projects
  • Presents principles that can be employed in applications ranging from software simulations to real-world web applications that serve millions of users
  • Contains a plethora of examples used to explain various interconnected concepts; most of the code samples on this website are editable and runnable in an interactive web-based IDE; for example, try editing this code snippet then run it.

Mohamed El-Geish's Projects

auc-plethora icon auc-plethora

This is a keepsake repo; the platform for which Plethora was built, Sun's "Project Looking Glass", is a now inactive

chainlit icon chainlit

Build Python LLM apps in minutes ⚡️

computing-with-data icon computing-with-data

Code samples for my book "Computing with Data: An Introduction to the Data Industry"

espnet icon espnet

End-to-End Speech Processing Toolkit

expann icon expann

Annotate code with an expiration date, and get a warning when it expires.

gooseberry icon gooseberry

A collection of common Go packages that Voicera uses in microservices

gradio icon gradio

Rapidly create UIs for prototyping your machine learning model in 3 minutes

llama_index icon llama_index

LlamaIndex is a data framework for your LLM applications

neural_sp icon neural_sp

End-to-end ASR/LM implementation with pytorch.

squad icon squad

Starter code for Stanford CS224n default final project on SQuAD 2.0

tester icon tester

Lightweight test utilities to use with Go's testing package

transformers icon transformers

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

tydiqa icon tydiqa

TyDi QA contains 200k human-annotated question-answer pairs in 11 Typologically Diverse languages and is designed for the training and evaluation of automatic question answering systems. TyDi QA's questions are written without seeing the answer and without the use of translation. This repository provides evaluation code and a baseline system for the dataset.

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