ignatiousanto

Cloud Architect | Data scientist | ML enthusiast

QuantiphiBangalore India

Pinned Repositories

-METOO_Mining
A project to mine data using the METOO hashtag on popular social media using python
00
basic-stuff
renderman shaders
00
CRAY
simple raytracer implementation
00
cv-tricks.com
Repository for all the tutorials and codes shared at cv-tricks.com
Language:Python00
Facial-Emotion-Detection-Using-Convolutional-Neural-Networks-and-Representational-Autoencoder-Units
This work showcases two independent methods for recognizing emotions from faces. The first method using representational autoencoder units, a fairly original idea, to classify an image among one of the seven different emotions. The second method uses a 8-layer convolutional neural network which has an original and unique design, and was developed from scratch. The models were trained on the JAFFE dataset, and we tested on a seperate JAFFE test set and a subjectively labeled Labeled Faces in the Wild data set.
Language:Python00
METOO_Mining
A project to mine data using the METOO hashtag on popular social media using python
Language:Python00
Sas-reporting-Automation
Set of macro function to automate report generation in SAS as an alternative to Proc tabulate
Language:SAS00
Tensor
Practice in tensor flow library for python
Language:Python00

ignatiousanto/METOO_Mining
A project to mine data using the METOO hashtag on popular social media using python
Language:Python
ignatiousanto/-METOO_Mining
A project to mine data using the METOO hashtag on popular social media using python
ignatiousanto/Tensor
Practice in tensor flow library for python
Language:Python
ignatiousanto/cv-tricks.com
Repository for all the tutorials and codes shared at cv-tricks.com
Language:Python
ignatiousanto/Facial-Emotion-Detection-Using-Convolutional-Neural-Networks-and-Representational-Autoencoder-Units
This work showcases two independent methods for recognizing emotions from faces. The first method using representational autoencoder units, a fairly original idea, to classify an image among one of the seven different emotions. The second method uses a 8-layer convolutional neural network which has an original and unique design, and was developed from scratch. The models were trained on the JAFFE dataset, and we tested on a seperate JAFFE test set and a subjectively labeled Labeled Faces in the Wild data set.
Language:Python
ignatiousanto/Sas-reporting-Automation
Set of macro function to automate report generation in SAS as an alternative to Proc tabulate
Language:SAS
ignatiousanto/CRAY
simple raytracer implementation
ignatiousanto/basic-stuff
renderman shaders