zaghlol94 Goto Github PK

followers: 27.0 following: 33.0 repos: 131.0 gists: 1.0

Type: User

Company: Netconomy

Bio: Computer science major passionate about Computer Vision,NLP, AI and machine learning

Location: Paderborn, NRW, Germany

Hi there, it's ZAG 👋

Hello! I'm ZAG, a Data Scientist and Machine Learning Engineer with a passion for bringing cutting-edge research in the fields of Machine Learning and Deep Learning to life in the software industry. I hold a Master's degree in Data Science (Computer Science) from Paderborn University and have dedicated myself to the mission of integrating the latest theoretical advancements into practical, scalable, and reliable data project pipelines.

My expertise lies at the intersection of academic theory and real-world implementation. I thrive on turning state-of-the-art models into robust solutions that excel in the dynamic landscape of data projects. With an extensive background in both the theoretical foundations and hands-on application of Machine Learning and Deep Learning techniques, I bring a unique blend of knowledge and experience to the table.

Over the course of my career, which spans five years, I have successfully deployed ML/DL solutions across a wide array of domains. Whether it's computer vision, natural language processing, recommendation systems, or any other area, I have consistently delivered results that meet the demands of modern data-driven industries.

My mission is to make the complex world of Machine Learning and Deep Learning accessible and practical for businesses and projects of all sizes. I believe that the power of data should be harnessed to its fullest potential, and I am here to help you navigate the journey from theory to scalable, reliable solutions.

Explore my GitHub repositories and discover how I can assist you in transforming your data challenges into opportunities for success. Together, we can bridge the gap between cutting-edge research and the practical implementation that drives innovation in today's data-driven world.

🔭 Paper that I have implemented from scratch ...
- Yolo V3, Show, Attend and Tell: Neural Image Caption Generation with Visual Attention, Convolutional Sequence to Sequence Learning, Sequence to Sequence Learning with Neural Networks, Attention Is All You Need, Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation, Neural Machine Translation by Jointly Learning to Align and Translate, U-Net: Convolutional Networks for Biomedical Image Segmentation, A Neural Algorithm of Artistic Style, Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks(DCGAN),
- Improved Training of Wasserstein GANs (WGANGP), Wasserstein GAN (WGAN), Conditional Generative Adversarial Nets (cGAN), Image-to-Image Translation with Conditional Adversarial Networks (PIX2PIX), Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (CycleGAN), Progressive Growing of GANs for Improved Quality, Stability, and Variation (ProGAN), Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (SRGAN).
🌱 I’m currently learning ...
- Generative AI
- Audio Signal Processing
📫 How to reach me: ...
- Linkedin
- Twitter
- Facebook
- Mail: [email protected]
😄 Pronouns: ...
- He/Him/His

zaghlol94's Projects

2012-us-election-analysis-

2012 General Election: Romney vs. Obama

ads-optimization-reinforcement-learning

Train model to know what the best ads to exploit using UCB algorithm --reinforcement learning

ai_curriculum

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

annotated_encoder_decoder

The Annotated Encoder Decoder with Attention

audio-classification

Code for YouTube series: Deep Learning for Audio Classification

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-deep-learning-papers

The most cited deep learning papers

awesome-deep-vision

A curated list of deep learning resources for computer vision

awesome-mlops

A curated list of references for MLOps

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-rl

Reinforcement learning resources curated

awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

awesome-speech-recognition-speech-synthesis-papers

Automatic Speech Recognition, Speaker Verification, Speech Synthesis, Language Modeling

awesome-vqa

Visual Q&A reading list

awesome_cv

Awesome educational list for computer vision (plus: machine learning, deep learning and data science)

captiongeneration

categorize-clustering-mall-customer

Clustering Mall Customer into groups depends on anual incom and spending score using K-Means algorithm

classifying-names-using-char-level

We will be building and training a basic character-level RNN to classify words. A character-level RNN reads words as a series of characters - outputting a prediction and “hidden state” at each step, feeding its previous hidden state into each next step. We take the final prediction to be the output, i.e. which class the word belongs to.

zaghlol94 Goto Github PK

Hi there, it's ZAG 👋

zaghlol94's Projects

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