fazel94 Goto Github PK
Name: Mohamad Fazeli
Type: User
Company: Maktabkhooneh.org
Location: Tehran, Iran
Mohamad Fazeli's Projects
api-client
A client for consuming content from the MediaCloud v2 API.
awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
backup_system_design_talk
Design of a Robust, Secure Backup System for Maktabkhooneh
clrs4th
📚 Solutions to Introduction to Algorithms Fourth Edition
ctci-6th-edition-python
Cracking the Coding Interview 6th Ed. Python Solutions
design-patterns-for-humans
Design Patterns for Humans™ - An ultra-simplified explanation
free-programming-books
:books: Freely available programming books
fucking-algorithm
手把手撕LeetCode题目，扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.
httpie
As easy as /aitch-tee-tee-pie/ 🥧 Modern, user-friendly command-line HTTP client for the API era. JSON support, colors, sessions, downloads, plugins & more. https://twitter.com/httpie
nlp
Natural Language Processing Best Practices & Examples
pyperformance
Python Performance Benchmark Suite
python-sortedcontainers
Python Sorted Container Types: Sorted List, Sorted Dict, and Sorted Set
scrapy-jsonrpc
Scrapy extension to control spiders using JSON-RPC
spherecluster
Clustering routines for the unit sphere
tastytoast
:bread: Make your native android Toasts Tasty
tehpugsessionsfiles
Repo for TehPUG Sessions Presentations Files
the-complete-faang-preparation
This repository contains all the DSA (Data-Structures, Algorithms, 450 DSA by Love Babbar Bhaiya, FAANG Questions), Technical Subjects (OS + DBMS + SQL + CN + OOPs) Theory+Questions, FAANG Interview questions, and Miscellaneous Stuff (Programming MCQs, Puzzles, Aptitude, Reasoning). The Programming languages used for demonstration are C++, Python, and Java.
tinygrad
You like pytorch? You like micrograd? You love tinygrad! ❤️
tweets
janky twitter replacement.
union_disjoint_sets
Python implemetation of Union of disjoint set data structures
wss2020_ml_persian_text
Code to accompany workshop "Machine Learning on Persian Text: Using Transfer Learning Word and Document Vectors(word2vec and doc2vec)" in WSS 2020
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