Ali Shakiba's Projects
Shared Nearest Neighbor-based Clustering by Fast Search and Find of Density Peaks
Solve sudokus from video in real time with computer vision and neural networks
Spatially-sparse convolutional networks. Allows processing of sparse 2, 3 and 4 dimensional data.Build CNNs on the square/cubic/hypercubic or triangular/tetrahedral/hyper-tetrahedral lattices.
Heart sound segmentation code based on duration-dependant HMM
SQLite compiled to JavaScript through Emscripten
دوره 12 ساعته یادگیری عمیق با چارچوب Keras
Software for "Quantum-Resistant Cryptosystems from Supersingular Elliptic Curve Isogenies"
Example Test Cases for Stanford's Algorithms Coursera Specialization
Stanford ACM-ICPC related materials
In-Memory Subgraph Matching: An In-depth Study by Dr. Shixuan Sun and Prof. Qiong Luo
Homework Submission, Automated Grading, and TA grading system.
Superset Quick Start Guide, published by Packt
A Python scikit for building and analyzing recommender systems
My experience with Telegram bots :)
Open source software library for numerical computation using data flow graphs.
Implementations of CNNs, RNNs, GANs, etc
Get started with TensorFlow's High-Level APIs (Just a very simple code for learning TensorFlow )
TensorFlow Tutorials with YouTube Videos
A crash course in six episodes for software developers who want to become machine learning practitioners.
Code for Tensorflow Machine Learning Cookbook
Tensorflow 2 Tutorials (use tensorflow and keras in a better way!)
Quite Practical and Far from any Theoretical Concepts- Learn python, Numpy, Pandas, Matplotlib, Seaborn, Scikit-learn
Tink is a multi-language, cross-platform library that provides cryptographic APIs that are secure, easy to use correctly, and hard(er) to misuse.
the goal is to predict the survival or the death of a given passenger based on 12 feature such as sex, age ,etc...
Tsunami is a general purpose network security scanner with an extensible plugin system for detecting high severity vulnerabilities with high confidence.
A Tutorial on Simple Machine Learning Methods Held for the Graduate School on Bionics, 2012
All my notes from the classes I've taken at UCLA