machine learning, deep learning, NLP, CV, RL

Egypt,Tanta

MOHAMED FAWZY ELAGAMY

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Employment

Education

Tanta

University of engineering

Fall 2014 – May 2019

Bachelor's degree in electronics and communication engineering, May 2014.

COURSES

. Computer Vision (object detection and classification,semantic segmentation,face recognition,generative adversarial network)

. machine learning Nanodegree (Decision Tree, SVM,Naïve Bayes, KNN, K-Means,Random Forest,,Dimensionality Reduction Algorithms,ensemble, GBM, cascaded model)

. deep learning (CNN,RNN,LSTM,DNN )

. Advanced deep learning algorithms ( variational autoencoder, gans, transfer learning,style transfer )

. Deep reinforcement learning Nanodegree (value based methods, police based methods, deep q learning,

police gradient methods, proximal police optimization, actor critic (A2C,A3C), multi agent reinforcement

learning, dynamic programming)

. NLP Nanodegree ( text classification, sentiment analysis, topic modeling,seq2seq, machine translation

with attention, chatbot )

. Data analysis and visualization

. feature engineering(Multivariate Missing Data Imputation, Categorical Variable Encoding, Variable

Transformation, Outlier Handling)

. statistics (probabilities and distributions)

. linear algebra

. calculus .

Technical Experience

Projects

machine learning projects classification and regression ( Decision Tree, SVM,Naïve Bayes, KNN, K-Means,Random Forest,Dimensionality Reduction Algorithms,ensemble, GBM, cascaded model)

Object classification and localization (YOLO) ( build the architecture and transfer learning the weights of the pre-trained yolo version 3)

Semantic segmentation (using pyramid scene parsing network and Cityscapes dataset)

GANs (SAGAN,BIGGAN with spectral normalization to generate faces)

Transfer Learning (transfer learning to fine tune some layers in pre-trained model)

Image Captioning ( using CNN and seq2seq model with attention)

Generate latent space for images like smiling vector eyeglass vector using variational autoencoder to generate some attribute features from the data)

Style Transfer in Fashion Industry using GANs (using CycleGan to transfer feature from one image to other)

machine translation using seq2seq with attention(translate text from language to other using seq2seq model and attention network)

Conversational AI Chatbots for Customer Service ( train chatbot to make conversation and answer questions)

Languages and Technologies

Python .

python packages numpy,pandas, matplotlib, seaborn .

opencv.

machine learning packages, scikit learn .

deep learning framworks,tensorflow, keras .

https://www.linkedin.com/in/mohamed-agamy-5453ab19a/

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