PROFILE OVERVIEW

I’m a machine learning and software

engineer, specialized in image

processing and computer vision

applications I had designed and

working on different application such

as object detection, image

recognition, image identification and

more, Also I had designed and

mentored different projects in different

international Competitions such as

Remotely Operated Vehicles ( ROV),

Minesweepers, Quad Copters and

more, Recently I’m an Author and

Instructor with packet publishing, trying

to teach students a real world projects

in a field of Machine learning/Deep

learning, Also I’m in a master of

science in electronics and

communications and signal

processing, my Research Interest is

computer Vision using CNN and

Natural language processing(NLP) in

bio-informatics field using

Deep/Machine learning.

CONTACT

PHONE:

+201*********

LinkedIn:

https://www.linkedin.com/in/mohame

d-elhaj-abdou-8b9559135/

EMAIL:

mohamedelsayedmohammed.2020@

gmail.com

Hobbies:

Chess

Video games

Ping-Pong

MOHAMED ELHAJ ABDOU

MACHINE LEARNING

EDUCATION

[Arab Academy for Science and technology]

[2012] – [2017]

[BSc Electronics and Communication Engineering, GPA: 3.1]

[Arab Academy for Science and technology]

[2018] – [Present]

[MSc Electronics and Communication Engineering]

WORK EXPERIENCE

[Naval Forces] [ORACLE Database Developer]

[January 2018]–[Present]

[as a reserve Navy Officer Service, I'm performing codes and scripts, in order to develop and creating reports and forms.]

[Udemy] [Author]

[Oct 2017]–[Present]

[teaching and creating online courses at packet publishing in machine learning and deep learning.]

PUBLICATIONS

[Real world Machine Learning Project's using TensorFlow]

[Nov 2018] [Video course]

[publication description Machine learning algorithms and research are mushrooming due to their accuracy at solving problems. This course walks you through developing real-world projects using TensorFlow in your ML projects.]

Course link:

Real World Machine Learning project using TensorFlow

[Getting started with Deep Learning in Practice]

[Jan 2020] [Video course]

[this is course one from five in Deep Tensor (DT) specialization, in this course we will going to take a real-world projects with TensorFlow 2 and deep learning, the course consists of five sections with five real world projects using TensorFlow 2 Framework.]

Course link:

Getting Started with Deep Learning in Practice

TRAININGS AND CERTIFICATIONS

[Machine Learning by Stanford University on Coursera]

[October 2017]– [November 2017]

[Neural Networks and Deep Learning by deeplearning.ai on Coursera]

[November 2017]– [December 2017]

[The Data Scientist’s Toolbox by Johns Hopkins University on Coursera]

[December 2017]- [Jan 2018]

[The Data Scientist’s Toolbox by Johns Hopkins University on Coursera]

[December 2017]- [Jan 2018]

[Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai on Coursera.]

[1 Jan 2018- 7]- [Jan 2018]

[Structuring Machine Learning Projects by deeplearning.ai on Coursera]

[8-Jan 2018]- [18 Jan 2018]

[R programming by Johns Hopkins University on Coursera]

[20-Jan 2018]– [26-Feb 2018]

[Aerial Robotics’ by university of Pennsylvania on Coursera.]

[30-Feb 2018]– [3-April 2018]

[Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai on Coursera.]

[1 Jan 2018]- [Jan 2018]

SKILLS

C [ embedded systems]

Python [TensorFlow, Pandas, Keras, pytorch, OpenCV, matplotlib…etc.] R [data analysis, statistical]

SQL/PLSQL [Forms, Reports]

MATLAB/Octave

GRADUATION PROJECT

My graduation project divided in to two major parts 1-Abstract (Swarm Robots Powered by Solar cells)

a Swarm-based solar-powered mine-detection for Minesweeper applications. In this paper, a multi robot systems is proposed along with reliable control architecture for swarm robots. Two solar operated ground vehicles operate in conjunction with a quad copter. A camera fixed on the quad copter takes image of the playground and detects surface mines. It also has the role of monitoring the behavior of the slaves. These slaves have the role of ensuring the true locations of the landmines viewed as well as detecting and localizing the buried mines in the field.

2- Abstract (Sensor fusion using Narx Neural networks) Sensor fusion is becoming an important method for low-cost and high- accuracy data processing techniques especially in risky environments and dangerous missions. Accurate fast availability of data from sensors is very important. This is why many methods and models were proposed in the Recent year’s researches. Those models depend on the type of data, errors, applications and surrounding environment around the sensor, dynamic changes. Non-linear statistics have their effects on the data too. a sensor fusion algorithm is proposed using non-linear artificial neural networks (Narx Model neural networks) to improve the position error of mobile robot during the mine detection mission. SELECTED PROJECTS

[agriculture quad copter used for fruits disease’s detection used image processing powered by Deep neural networks]

[10-14 April 2019]

[from the best invention’s over the world in 47

Salon international des

inventions des GENEVE]

[Minesweeper landmine free]

[January 2016]– [October 2016]

[8th place Egyptian National Competition Minesweeper 2016.]

[Minesweeper landmine free]

[January 2017]– [October 2017]

[11th place Egyptian National Competition Minesweeper 2017.]

Contact this candidate