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ad_examples

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

arabic_text_summarization

Arabic Extractive Text Summarization

awesome-public-datasets

An awesome list of high-quality open datasets in public domains (on-going).

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

churn-dataset-analysis-

(In Progress) Baisc Analysis of Churn Dataset Using Pandas

command-line-image-classifier

Command Line Image Classifier using pytorch pretrained netwroks

competitive-data-science

Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course

compression-algorithms-implementation

java Implementation for famous Compression Algorithms

concrete-autoencoders

cs231n_assignments

cs231n Spring 2019 coding assignments solution

data-leakage

Data Leakage Programming Assignment for "How to win a data science competition" Coursera course.

datasciencecourse

This holds iPython notebooks and lecture slides for the Intro to Data Science Master's course I teach at NYU.

dynamic-kg

Dynamic (Temporal) Knowledge Graph Completion (Reasoning)

efficient-dl-systems

Efficient Deep Learning Systems course materials (HSE, YSDA)

ensembling

Ensembling Programming Assignment for "How to win a data science competition" Coursera course.

ganhacks

starter from "How to Train a GAN?" at NIPS2016

good-papers

I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers

hadron-collider-machine-learning

Materials for "Addressing Large Hadron Collider Challenges by Machine Learning" Coursera MOOC

interactive-coding-challenges

120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.

ipython-notebooks

A collection of IPython notebooks covering various topics.

kadenze-deep-creative-apps

Kandenze creative applications of deep learning in TensorFlow assignments

kaggle_1c_competition

This challenge serves as final project for the "How to win a data science competition" Coursera course. In this competition you will work with a challenging time-series dataset consisting of daily sales data, kindly provided by one of the largest Russian software firms - 1C Company. We are asking you to predict total sales for every product and store in the next month. By solving this competition you will be able to apply and enhance your data science skills.

keras

Deep Learning for humans

leetcode

Complete solutions to Leetcode problems; updated daily. (I'm looking for long-term contributors/partners to this repo! Send me PRs if you're interested! - 9/5/2018)

machine-learning-collection

Traditional Machine Learning and Deeplearning using Pytorch

mean_encoding

Mean Encoding Programming Assignment for "How to win a data science competition" Coursera course.

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

nlp-mini-projects

various nlp tasks (Arabic tasks on KALIMAT dataset)

notebooks

Jupyter notebooks for the Natural Language Processing with Transformers book

orlian-source-code