ajaafer Goto Github PK

1.python-tutorial-for-beginners-full-course-2019

aj4.github.io

My online portfolio website

ajaafer.github.io

amazon-product-reviews

This is my Data Analytics Project with Python: Insights from Amazon Product Reviews in Data & Program Analytics class taught by professor Tingting Nian at UCI Paul Merage school of business on March 2017. Techniques: Exploratory Data Analysis, Web Scraping, Natural Language Processing, Predictive Modeling.

amazon-review-scraper

A python library to scrape data from amazon.com

anomaly-detection-resources

Outlier detection books, papers, videos, and implementations

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

bitcoin-value-predictor

Predicting Bit coin price using Time series analysis and sentiment analysis of tweets on bitcoin

breast-cancer-ml-r

Introduction to Machine Learning Techniques in R Using Breast Cancer Data

cfrbm

CFRBM is a implementation of the RBM model to the collaborative filtering task

conditional_generative_adversarial_rnns

Conditional Generative Adversarial Recurrent Neural Networks implemented with Tensorflow

credit-card-fraud-detection-on-transactions

Fraud Detection Using Outlier Detection Tools

credit-card-fraud-detection-parallelized-bayesian-network

Machine Learning Classification Project: Credit Card Fraud Detection using Parallelized Neural Networks

creditcardfrauddetection

A COMBINED APPROACH OF SMOTE DATA BALANCING WITH DATA MINING ALGORITHMS FOR DETECTING CREDIT CARD FRAUD. Fraud detection method are Support Vector Machines(SVM), K-Nearest Neighbour algorithm(KNN). These techniques can be used alone or meta learning techniques to build classifiers. But amongst all existing method, ensemble learning methods are identified as populate and common method, not because of its quite straightforward implementation, but also due to its exceptional predictive performance on practical problems.

cscs-530-w2016

Complex Systems 530 - Computer Modeling of Complex Systems (Winter 2016)

data-analysis-with-r

Using gglot2, tidyr, dplyr, ggmap, choroplethr, shiny, logistic regression, clustering models and more

dataminingwithr

Data Mining with R - Learning with Case Studies

ddp_shiny

Shiny application for Interactive Machine Learning

detecting-fraudulent-credit-card-transactions

Trained a Isolation Forest anomaly detection algorithm which gave 96.5% accuracy in predicting fraudulent transactions on test set.

devportfolio

A lightweight, customizable single-page personal portfolio website template built with JavaScript and Sass

dp_means

Dirichlet Process K-means

driver_behaviour_monitor

To monitor driver behavior, based on rate of acceleration/deceleration and to predict parking availability based on crowd sourcing the data.

ebooks

Books, Articles, Papers and Slides

eeg-datasets

A list of all public EEG-datasets

example-models

Example models for Stan

fraud-analysis

Insurance fraud claims analysis project

gan-rnn_timeseries-imputation

Recurrent GAN for imputation of time series data. Implemented in TensorFlow 2 on Wikipedia Web Traffic Forecast dataset from Kaggle.

generative-adversarial-networks-for-financial-time-series-generation

hands-on-artificial-intelligence-for-iot

Hands-On Artificial Intelligence for IoT, published by Packt