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abstractionautomation

age-gender-estimation

Age estimation is the determination of a person’s age based on biometric features. Although age estimation can be accomplished using different biometric traits, our work is focused on facial age estimation that relies on biometric features extracted from a person’s face. In the area of computerized analysis of facial images for recognition, ethnicity classification, gender recognition, etc. the age estimation is a barely explored part. However recently the interest in this subject has significantly increased, due to its practical applications. For example there are age limitations for driving a car, buying alcohol, cigarettes, films, video games, etc. which should be obeyed, but the human skills of age estimation are very limited. So a computer system, which supports the responsible persons, would be helpful. It is well known that the human-computer interaction varies for different age groups, thus a system which automatically adapts its interface to the age of the current user would clear this problem. Face detection: To detect whether an image represent a face i.e. the general structure of face or not. General structure include forehead, eyes, nose, lips, chin etc.

atlas

ATLAS is an open source software tool for researchers to conduct scientific analyses on standardized observational data

cliner

Clinical Named Entity Recognition system (CliNER) is an open-source natural language processing system for named entity recognition in clinical text of electronic health records.

commondatamodel

Definition and DDLs for the OMOP Common Data Model (CDM)

covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

covid-tracking-data

cqf-ruler

CQL Measure Processing Component

cython

A Python to C compiler

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data_analysis_with_python_and_pandas

The Code belonging to my course "Data Analysis in Python and pandas"

deep-air

Predicting Air Pollution in Beijing, China using Deep Neural Nets

deep-learning-processor-list

A list of ICs and IPs for AI, Machine Learning and Deep Learning.

etl-cms

Workproducts to ETL CMS datasets into OMOP Common Data Model

face-expression-and-ethnic-recognition

Two image models for face expression recognition and for ethnic classification

gospel-of-health-notebooks

Notebooks for A Gospel of Health and Salvation

gt-fhir

Georgia Tech FHIR Server Web Page

ibm.github.io

Portal for IBM open source at GitHub

icps

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

keras2cpp

This is a bunch of code to port Keras neural network model into pure C++.

learnopencv

Learn OpenCV : C++ and Python Examples

machine-learning-links-and-lessons-learned

List of all the lessons learned, best practices, and links from my time studying machine learning

matconvnet

MatConvNet: CNNs for MATLAB

matplotlib

matplotlib: plotting with Python

mica-race-from-face

Predicting race from faces for movie data

mmlspark

Microsoft Machine Learning for Apache Spark

mnist-dataset-in-different-formats

Just a MNIST dataset in different formats

models

Models and examples built with TensorFlow

multivariate-time-series-forecast-using-seq2seq-in-tensorflow