babayefarzan Goto Github PK

hezar

The all-in-one AI library for Persian, supporting a wide variety of tasks and modalities!

hmm-moment-classification

Generative classification of discrete time series using Hidden Markov Models and a composite likelihood based on third-order moments

inventory-ai

Inventory-Production problem using reinforcement learning.

ipythonscripts

Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning

keras-resources

Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library

leaf-classification

Kaggle Competition | The objective of this competition is to use binary leaf images and extracted features, including shape, margin & texture, to accurately identify 99 species of plants. Leaves, due to their volume, prevalence, and unique characteristics, are an effective means of differentiating plant species.

learnopencv

Learn OpenCV : C++ and Python Examples

loan-default-prediction-and-suggesting-best-investment-strategy

This a case study done in series of three phases. We have used over 10years of lending club loan data. Phase-1: Identified useful attributes, and brainstormed various questions one can solve with the given data. Phase-2: Data cleaning, transformation, and exploratory data analysis. Created a clean-data pickle file. Phase-3: Built a predictive machine learning model. Tested for robustness on different data (but same source), and chose random forests to be the best model with 80% roc-auc score. Tested and trained models with 100 test/train splits for more robustness and accuracy. Once we got the best classifier, we have applied various regression techniques to choose the best investment strategy out of 4 pre-defined strategies. Please feel free to fork, merge the code. Contact me for data.

medium_notebook

Repository containing notebooks of my posts on Medium

ndvi_prediction

Using Neural Networks to predict Normalized Difference Vegetation Index based on precipitation and temperature estimates.

nyc_yl5240

old_vegindex

Python package to generate vegetation index timeseries from PhenoCam images.

opportunity-zones

Generated while working on SEEDS II Solar Opportunity Zones

opportunity-zones-investment-app

Opportunity Zones Investment App

opportunity_zones

Exploration of Opportunity Zones

opportunity_zones-1

opportunityzone

oracledatasciencehackathon2019

On 20-21 March, I teamed up with a group of guys and tackled a challenge at a local Hackathon. We did a sentiments analysis on The Big Four Agenda launched by our current President, Uhuru Kenyatta, so as to determine howKenyans responded to the four main pillars this are: Universal Health Care, Food Security, Affordable Housing and Manufacturing. We collected data from twitter using tweepy and did the sentiment analysis using TextBlob

payamnorouzzadeh.github.io

Payam Norouzzadeh's Website

pic2vec

Lightweight package for featurizing images

plantcv-workshop

PlantCV Workshops

plotly_ipywidget_notebooks

pre-diabetes-prediction-using-machine-learning

This jupyter notebook code predicts whether a person has pre-diabetes or diabetes. I have used NHANES data to train and test the model using various classifiers. An extensive feature engineering has been done to determine the most relevant features to diabetes. Brought down 1645 features to 25 most relevant features using various machine learning techniques. I want to improve this further. Please feel free to fork, merge the code.

predicting-poverty

Combining satellite imagery and machine learning to predict poverty

project_suite_machine_learning

The machine learning application will predict house price for a location based on the influential factors like household income, population and total number of houses, house inventory for sale, unemployment rate, poverty rate etc.

ptsd

Yair Bar Haim Lab

ptsd-data-analysis-research

These codes are my work toward my PhD to understand Post Traumatic Stress Disorder (PTSD) in people who suffer from this disorder. I hope my research and analysis can help this population live a better life and access to better care. Codes are in R and Python primarily.

ptsd-patient-analysis

Machine Learning approaches

ptsd_syntax

PTSD identification using nlp

pui2017_ses515

Python exercises from NYU Urban Informatics course, 2017