Personal Information
Organization / Workplace
Copenhagen Area, Capital Region, Denmark Denmark
Occupation
Author, Data Scientist, Engineer (Deep learning - Computer Vision)
Industry
Technology / Software / Internet
About
Amgad has more than 11 years of experience with a professional altitude grounded in the cross-cutting knowledge and practice of both data science and engineering. With strong leadership and the capacity to work as a team player, Amgad helped teams to implement and deliver different machine learning systems utilizing stat-of-the-art deep learning architectures in different disciplines including computer vision and NLP.
Amgad is also a published author focusing on helping software developers to build vision-aware and intelligent applications.
Tags
machine learning
deep learning
object detection
cnn
computer vision
gpu
cuda
caffe
dnn
law of large numbers
pca
autoencoder
best practices
mobile development
performance
android
unsupervised feature learning
sparse-auto encoders
gfs
distributed file systems
python
dynamic typing
See more
Presentations
(7)Likes
(1)Fighting financial fraud at Danske Bank with artificial intelligence
Ron Bodkin
•
6 years ago
Personal Information
Organization / Workplace
Copenhagen Area, Capital Region, Denmark Denmark
Occupation
Author, Data Scientist, Engineer (Deep learning - Computer Vision)
Industry
Technology / Software / Internet
About
Amgad has more than 11 years of experience with a professional altitude grounded in the cross-cutting knowledge and practice of both data science and engineering. With strong leadership and the capacity to work as a team player, Amgad helped teams to implement and deliver different machine learning systems utilizing stat-of-the-art deep learning architectures in different disciplines including computer vision and NLP.
Amgad is also a published author focusing on helping software developers to build vision-aware and intelligent applications.
Tags
machine learning
deep learning
object detection
cnn
computer vision
gpu
cuda
caffe
dnn
law of large numbers
pca
autoencoder
best practices
mobile development
performance
android
unsupervised feature learning
sparse-auto encoders
gfs
distributed file systems
python
dynamic typing
See more