Mohamed Zumair (mhdzumair)

mhdzumair

Geek Repo

Company:Pearson

Location:Sri lanka

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Mohamed Zumair's starred repositories

celery

Distributed Task Queue (development branch)

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magenta

Magenta: Music and Art Generation with Machine Intelligence

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playwright-python

Python version of the Playwright testing and automation library.

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fastapi-best-practices

FastAPI Best Practices and Conventions we used at our startup

geckodriver

WebDriver for Firefox

reptyr

Reparent a running program to a new terminal

oh-my-bash

A delightful community-driven framework for managing your bash configuration, and an auto-update tool so that makes it easy to keep up with the latest updates from the community.

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reloadium

Hot Reloading and Profiling for Python

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furo

A clean customizable documentation theme for Sphinx

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beanie

Asynchronous Python ODM for MongoDB

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MyExpenses

GPL licenced Android Expense Tracking App

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firefox-sweet-theme

:candy: A dark and modern theme for firefox with vibrant colors

django-leaflet

Use Leaflet in your Django projects

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ntfy-android

Android app for ntfy.sh

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Forensic-Tools

A collection of tools for forensic analysis

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flask-material-dashboard

Flask Dashboard - Material Design | AppSeed

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MediaFusion

Universal Stremio Add-On

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deezer-python

Deezer client for python

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acoustid-server

AcoustID's web site and API

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music-generator

Machine Learning group project

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tamilblasters_stremio_addon

Stremio Addon for TamilBlasters Movies.

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sample-flask-auth-session

Flask User Authentication - Open-source Sample | AppSeed

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stremio-beamup-cli

CLI for deploying to Beam Up servers

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tamilyogi_stremio_addon

Stremio Addon for TamilYogi Movies.

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cvae-chord-generation-complexity

Modeling Harmonic Complexity using two models of Conditional Variational Autoencoders - MSc. Thesis

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firefox-lambda

A Lambda container image that provides a Playwright-patched version of Firefox

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deezer-playlist-generator

:musical_note: Library for working with Deezer API for creating a playlist by your preferences in Deezer

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GitAIOps

ChatGPT plugin that enables ChatGPT to interact with Git services

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Coursera-Introduction-to-Big-Data-by-University-of-California-San-Diego

<h1>hare krishna</h1> Here’s an overview of our goals for you in the course. After completing this course you should be able to: - Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. - Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. - Get value out of Big Data by using a 5-step process to structure your analysis. - Identify what are and what are not big data problems and be able to recast big data problems as data science questions. - Provide an explanation of the architectural components and programming models used for scalable big data analysis. - Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. - Install and run a program using Hadoop! Throughout the course, we offer you various ways to engage and test your proficiency with these goals. Required quizzes seek to give you the opportunity to retrieve core definitions, terms, and key take-away points. We know from research that the first step in gaining proficiency with something involves repeated practice to solidify long-term memory. But, we also offer a number of optional discussion prompts where we encourage you to think about the concepts covered as they might impact your life or business. We encourage you to both contribute to these discussions and to read and respond to the posts of others. This opportunity to consider the application of new concepts to problems in your own life really helps deepen your understanding and ability to utilize the new knowledge you have learned. Finally, we know this is an introductory course, but we offer you one problem solving opportunity to give you practice in applying the Map Reduce process. Map Reduce is a core programming model for Big Data analysis and there’s no better way to make sure you really understand it than by trying it out for yourself! We hope that you will find this course both accessible, but also capable of helping you deepen your thinking about the core concepts of Big Data. Remember, this is just the start to our specialization -- but it’s also a great time to take a step back and think about why the challenges of Big Data now exist and how you might see them impacting your world -- or the world in the future!

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