sheikhrabiul Goto Github PK

a-deep-learning-based-illegal-insider-trading-detection-and-prediction-technique-in-stock-market

Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock market. In this work, we present an approach that detects and predicts illegal insider trading proactively from large heterogeneous sources of structured and unstructured data using a deep-learning based approach combined with discrete signal processing on the time series data. In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns. My research paper (IEEE Big Data 2018) on this can be found here: https://arxiv.org/pdf/1807.00939.pdf

awesome-machine-learning-interpretability

A curated list of awesome machine learning interpretability resources.

awesome-machine-learning-operations

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

black-box-explainability

caesar_cipher_decryption_brute_force

Breaking caesar cipher using brute force attack.

casebasedreasoning

Find missing values in data set using Euclid distance, normalization and calculating information value, weight of evidence

cicflowmeter

CICFlowmeter-V4.0 (formerly known as ISCXFlowMeter) is a network traffic Bi-flow generator and analyzer for anomaly detection that has been used in many Cybersecurity datsets such as Android Adware-General Malware dataset (CICAAGM2017), IPS/IDS dataset (CICIDS2017) and Android Malware dataset (CICAndMal2017).

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

covid-19-data

An ongoing repository of data on coronavirus cases and deaths in the U.S.

credit-risk

ctci-6th-edition-python

Cracking the Coding Interview 6th Ed. Python Solutions

ctci-solutions

Python solutions to Cracking the Coding Interview (6th edition)

data-science-blogs

A curated list of data science blogs

data-science-cheatsheet

datastructureandalgorithms

Write code that run faster, use less memory and prepare for your Job Interview

deeplearningtutorials

Deep Learning Tutorial notes and code. See the wiki for more info.

domain-knowledge-aided-explainable-ai-for-intrusion-detection-and-response

evolutionary-algorithm

Evolutionary Algorithm using Python

explainability-and-bias

free-data-science-books

Free resources for learning data science

gamo

Generative Adversarial Minority Oversampling

gans-for-imbalanced-data-generation

geneticalgorithm

A genetic algorithm for selecting optimal feature combinations with sklearn supervised ML objects

iml

iml: interpretable machine learning R package

interpret

Fit interpretable models. Explain blackbox machine learning.

interpretable-ml-book

Book about interpretable machine learning

karoo_gp

A Genetic Programming platform for Python with TensorFlow for wicked-fast CPU and GPU support.

machine_learning_examples

A collection of machine learning examples and tutorials.

machinelearning

Implementation of a Machine Learning Algorithm [ decision-tree learning, the algorithm is taken from the book Artificial Intelligence, A Modern Approach --Russell and Norvig]

mining_bad_credit_card_accounts

This is a web based software interface [ using Python, Flask, Scikit-learn, Sqlite3, D3js, Ajax, HTML and CSS ] for the research work titled "Mining bad credit card accounts from OLAP and OLTP system".