5
1
Egypt
1 year of experience
software engineer with a focus on artificial intelligence and machine learning. Throughout my academic journey, I’ve cultivated a strong foundation in computer science, and I’ve had the opportunity to apply these skills in practical settings. During my time as a student, I actively sought out projects that allowed me to explore the intersection of AI and software development. For instance, I engaged in a collaborative effort to develop a predictive analytics model for TimeSeries problem . This experience not only honed my programming skills but also sparked my passion for leveraging AI to solve real-world challenges. I also undertook internships that provided hands-on experience in implementing machine learning algorithms. In one particular internship, I contributed to the development of a recommendation system that significantly improved user engagement. This experience allowed me to apply my theoretical knowledge in a professional setting and exposed me to the intricacies of deploying machine learning models in a production environment. Drowness detection while divring (https://github.com/abdalrahmenyousifMohamed/Drowness-Detection-OpenCV) - Low back pain |Lumber spain detection by values provided by sensors is placed in back of patient or MRI data (https://github.com/abdalrahmenyousifMohamed/LBP) - TwiteGenius a groundbreaking startup at the intersection of AI and social media(https://github.com/abdalrahmenyousifMohamed/TwitGenius)
Parses pdf with pypdf Index Construction with LlamaIndex's GPTSimpleVectorIndex the text-embedding-ada-002 model is used to create embeddings see vector store index page to learn more indexes and files are stored on s3 Query the index uses the latest ChatGPT model gpt-3.5-turbo local mode for app (no s3) global variable use_s3 to toggle between local and s3 mode deploy app to streamlit cloud have input box for openai key uses pyarrow local FS to store files update code for new langchain update Custom prompts and tweak settings create a settings page for tweaking model parameters and provide custom prompts example Add ability to query on multiple files Compose indices of multiple lectures and query on all of them loop through all existing index, create the ones that haven't been created, and compose them together