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Hi there šŸ‘‹

  • šŸ”­ Iā€™m currently working on Deep Learning project for Trust Systems company
  • šŸŒ± Iā€™m currently learning Data science and deep learning

eslamhosam's Projects

100-days-of-ml-code icon 100-days-of-ml-code

A day to day plan for this challenge. Covers both theoritical and practical aspects

applied-ml icon applied-ml

šŸ“š Papers & tech blogs by companies sharing their work on data science & machine learning in production.

best-of-ml-python icon best-of-ml-python

šŸ† A ranked list of awesome machine learning Python libraries. Updated weekly.

data icon data

Data and code behind the articles and graphics at FiveThirtyEight

deep-learning icon deep-learning

Practicing Python for Deep Learning with Tensorflow 2 library and Keras

ds-projects icon ds-projects

containing dataquest.io projects for data science track a beginner friendly projects to learn data science including (data analysis, EDA, SQL, ML)

german-traffic-sign-classification-using-tensorflow icon german-traffic-sign-classification-using-tensorflow

In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.

handson-ml2 icon handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

handson-ml3 icon handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

llm-course- icon llm-course-

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

machine-learning-projects icon machine-learning-projects

this repo including beginner friendly Machine learning projects (regression/ classification) to do some practice with sickit learn library

ml-foundations icon ml-foundations

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

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