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Hi 👋, I'm Ahmed Emam

Machine learning researcher and PhD. candidate at the University of Bonn

ahmedemam_de

Introduction to XAI Tutorials on my channel

  • Tutorial 1: Explainable machine learning: Introduction - In this tutorial, I provide an introduction to explainable machine learning concepts.

  • Tutorial 2: visualize activations of convolutional layers in a neural network - I'm explaining the concept of feature maps and how they can be used to visualize how your data is behaving.

  • Tutorial 3: Saliency Maps - we'll be using Saliency Maps to explore the emotional content of a video. We'll be using the Saliency Map to look for interesting topics, people, and emotions in the video and to find patterns in the data.

  • Tutorial 4: Occlusion sensitivity - The video shows "Which Pixels in an image influence the neural network's decision" discusses how to identify the pixels in an image that impact the decision-making process of an artificial neural network. The video explains in detail how computer vision and neural network techniques can be used to determine the important pixels in an image that the smart system focuses on while making decisions.

Connect with me:

ahmedemam_de ahmed emam ahmademam576 ahmedemamai

Languages and Tools:

bash cplusplus git linux opencv pandas python pytorch scikit_learn seaborn tensorflow

ahmedemam576

Ahmed Emam's Projects

confident_explanations icon confident_explanations

Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness in Fennoscandia with Confidence

excelnumericaldemos icon excelnumericaldemos

A set of numerical demonstrations in Excel to assist with teaching / learning concepts in statistics and geostatistics.

neuralsolvers icon neuralsolvers

Neural network based solvers for partial differential equations.

prettymaps icon prettymaps

A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.

spacex icon spacex

we use activation maximization and GANs to discover patterns that contributes to the concept of naturalness in satellite imagery

testing icon testing

to test the link between git and the r studio

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