Ali Shakiba's Projects
π’ Ready to learn!β
you will learn 10 skills as data scientist:π Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.π
I want to solve Iris problem (Hello World) a popular machine learning Dataset as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template to deal with machine learning problems.
Materials for Applied Data Analysis CS-401, fall 2020
500 Lines or Less
πΏ Web-based Windows 98 desktop recreation ββββββββββββββββββποΈποΈποΈ
This tutorial demonstrates the basic workflow for Deep Learning.You should be familiar with basic linear algebra,Python and the Jupyter Notebook editor. It also helps if you have a basic understanding of Machine Learning and classification.
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Build a Jekyll blog in minutes, without touching the command line.
An implementation of the Advanced Encryption Standard (AES) algorithm meant for study to go along with "A Stick Figure Guide to the Advanced Encryption Standard (AES)" blog post at www.moserware.com
Some of the ML and DL related reading materials, research papers that I've read
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Applied Deep Learning Course
Approaching (Almost) Any Machine Learning Problem
ARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy.
Notes and Labs for Advanced Topics in Data Processing
Examples of autograders for running on Gradescope
:books: List of awesome university courses for learning Computer Science!
A collection of important graph embedding, classification and representation learning papers with implementations.
A topic-centric list of high-quality open datasets in public domains. Propose NEW data βββPRβββ
Job Guy Backend
Sample Code for βSequential and Parallel Algorithms and Data Structures -- The Basic Toolboxβ Book
A python tutorial on bayesian modeling techniques (PyMC3)
Homepage for STAT 157 at UC Berkeley
CS 451/651 Data-Intensive Distribute Computing (Fall 2018) at the University of Waterloo