Yousra Hazem Mohamed, MASc

One good news: one of my research papers gets accepted in ICSE-2025 (research track). The title of the paper is “Ranking Relevant Tests for Order-Dependent Flaky Tests”. #ICSE2025, #LLM, #testing, #ottawa - #Canada

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Thank you Francisco Yirá A. for trying out Squirrels and sharing your thoughts on the framework! While I initially created the API framework to get around the complexities of engineering dataset APIs for embedded analytics, it's amazing to see others believe that the solution can be applied to many data science use cases as well! I also think the recently added features of dashboard APIs and ability to interact with a Squirrels project in a Jupyter Notebook can be valuable for data scientists.🙂 If anyone has any questions about Squirrels, feel free to DM me! It's free to use with a simple "pip install" in Python. A tutorial can be found here: https://lnkd.in/gAJ_9duz

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I will be speaking on Data Privacy and Responsible AI on this AI Symposium

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To Label or to Pseudo Label? Active Learning vs Semi-Supervised Learning: I'm thrilled to share that as H3M Analytics, our Mitacs collaboration with the University of Ottawa has resulted in our first paper being published in this project at the The 37th Canadian Conference on Artificial Intelligence! The paper, co-authored by Bahar Afshar, Paula Branco, Utku Gorkem Ketenci, and Hikmet Mazmanoglu, explores the effectiveness of Active Learning and Semi-Supervised Learning methods for Windows malware detection. Using the Microsoft malware prediction dataset, we found that both methodologies enhance detection accuracy, especially in scenarios with limited labeled data, with Semi-Supervised Learning showing superior outcomes in certain settings. For more details, check out the paper here: https://lnkd.in/eK2gTE7d #Research #Innovation #AI #Compliance

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In case you missed it, Liz Lozinsky and I presented on Fuel iX, our enterprise-grade Gen AI platform, at the Toronto Machine Learning Summit. You can watch the recording here: https://lnkd.in/gN7e9XCv Also, don't miss out on our Chief Insights and Analytics Officer Jaime Tatis's talk on 'How Is GenAI Reshaping Business.' Catch it here: https://lnkd.in/gDWMAq6D

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Just did a keynote in PyTorch conference, on LLM deployment. Thanks for the great work of PyTorch team, our partners, and the interests from the audience! Please try out our deployment ecosystem of torchchat, torch.compile, torch.export, AOT Inductor, torchao and ExecuTorch, and checkout all the amazing talks, posters and demos in the conference!

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Meet our Grocer - Grocery AI Agent to create hyper personalized grocery list. 😀 Powered by Gen AI, balanced on groundedness & creativity,compound agent. We (Team Neuron from Sobeys) are excited to present our submission for Databricks Gen-AI hackathon-2024. Mark Babij Wilson Chan Simon Doubt Amir Tavasoli Graeme Crawley Akhil Goyal Balakrishna Kesavan Dheeraj Sarwaiya Alexander Terado Manjunatha Gopinath Rao Mohit Grover Sai Sahas Elluru #genai #ai #hackathon #llm #datascience #llama #mistral #canada LangChain MLflow

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Continuing my journey to understand and build deep learning models, I've decided to build a model to try and predict daily AQI values in my city, Montreal. The model was trained on roughly 10 years' worth of data of past AQI and weather related data such as precipitation, temperature and humidity. Overall, I'm getting an accuracy of approximately 76% over the last year (may 2023 to may 2024) which is better than what I expected, considering this is the first time I've built models around structured data. My next steps are writing up a blog post and open sourcing the accompanying Jupyter notebook then tweaking the model to predict future values! Check it out here: https://tlbvr.com/lab/aqi/

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Microsoft Research introduced OmniParser – a breakthrough in multimodal large model for GUI agents, now available on Hugging Face! OmniParser is a compact screen parsing module that leverages the power of large vision-language models like GPT-4V to transform UI screenshots into structured elements. This enables AI agents to interact with user interfaces (UI) effectively using purely visual inputs. With OmniParser, researchers are able to tackle some of the toughest challenges in GUI-based agent technology: Reliable identification of interactive icons within the UI. Deep understanding of UI semantics to accurately map actions to specific regions on the screen. Powered by models like GPT-4V, OmniParser takes intelligent agents to the next level, enabling them to perform precise actions across diverse operating systems and applications. In fact, it recently achieved top performance in the WindowsAgentArena benchmark! 🎉 OmniParser is now available open-source on GitHub!  https://lnkd.in/gZge9yta It's an interesting read for vision language model researchers and enthusiasts. #MicrosoftResearch #AI #MachineLearning #VisionLanguageModels #OmniParser #GPT4V #HuggingFace #ArtificialIntelligence #UserInterface #ScreenParsing

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In my latest blog post, I explore three powerful frameworks in the AI space: LangChain, LlamaIndex, and Llama Stack. I explain how each tool functions, their unique features, and the specific use cases they cater to. The blog also compares their market presence, highlighting their strengths and ideal applications in natural language processing. Article: https://lnkd.in/e55HFP-U

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If you didn't have a chance to attend my Getting Started with Generative Text & Fine-tuning LLMs in Hugging Face workshop at Toronto Machine Learning Society (TMLS) Toronto Summit last month, all of the content is now available online! 🚀 Highlights of the workshop include: 💡 An intro to #largelanguagemodels and generative text models in #HuggingFace 🤗 🌡️An explanation of different decoding strategies for #LLMs (temperature, top-p, top-k, beam & greedy search) ⚙️Fine-tuning GPT-2 medium to talk like a Jedi Master 😱Using LoRA to fine-tune GPT-XL using only a Google Colab free instance 🙊Throwing shade at AGI, in-context learning, and George Lucas Check out the full 90 minute video of the workshop here 📽️: https://lnkd.in/gh5aXy4Q View the workshop materials on Github🧑‍💻: https://lnkd.in/gb7aKSCU Give the code a spin for yourself in Google Colab 🧪: https://lnkd.in/gvnpZWSu

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Excited to share the OpenNLP Labs Global Symposium on Inclusive NLP with my community!  This event on September 14th at 1:30 PM PST is all about bridging innovation and inclusion in AI. Whether you're a researcher, student, or industry leader, there's something valuable for you here. Let’s work together to create a more inclusive future in AI! #NLP #AIResearch #AI #InclusiveAI

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AI-Powered Search: Embedding-Based Retrieval and Retrieval-Augmented Generation (RAG) https://bit.ly/3y09rJy #AI #MachineLearning #DeepLearning #LLMs #DataScience

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Explore How Relationships Can Be a Catalyst for Personal Growth and Positive Change - in Kitchener/Waterloo Join us for a free lecture, "Ethical principles in human relationships: Learning with each other," part of the series "Logosophy: Transforming the world starting from yourself." Wednesday, July 17 at 5:15 pm EDT at the Waterloo Public Library - Canada This engaging session delves into the transformative power of human connection. We'll explore how personal and professional relationships can be a springboard for self-improvement and ethical living. The lecture will unpack the concept of "learning with each other," highlighting how our interactions with others offer opportunities for growth and reflection. Discover practical tools and principles for fostering ethical connections, fostering empathy, and building stronger, more meaningful relationships. Through interactive exercises and insightful discussion, you'll gain a deeper understanding of how your relationships can contribute to your personal evolution and, ultimately, to a more positive and connected world. This lecture is ideal for anyone interested in personal development, building stronger relationships, and creating a more positive social environment. Check the details and RSVP today at https://lnkd.in/e7QYDDXu #logosophy #selfimprovement #waterloo #kitchener #kitchenerwaterloo #consciousliving #personalgrowth #community #transformation #lecture #makingabetterworld #freepubliclecture

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I've been wanting to try variational autoencoders (VAE) for quite some time, and I was lucky to attend the Compute Ontario summer courses, which offered a course on Deep Learning. I focused on the MNIST dataset, using Python and Tensorflow to model and create a VAE with the MNIST dataset, and the results looked really cool! Variational autoencoders are special types of ML architectures that aim to learn the multivariate distribution of our data. Because of its capacity to retrieve an abstraction of the data's distribution, known as a latent space, it is possible to sample from this data to generate new information.

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🌟 Exciting News! Join Us at BuildAI 2024: Perception Matters 🌟 📅 When: May 10th - 13th, 2024 📍 Where: Vancouver, London, and virtual 🔗 Register Now: Are you ready to dive into the world of artificial intelligence? Look no further! The BuildAI 2024 hackathon is your chance to turn an idea into a prototype and connect with like-minded innovators. Whether you’re an AI enthusiast, developer, or just curious about the possibilities, this event is for you. Why Attend? 54 Hours of Intense Creativity: From Friday evening to Sunday afternoon, immerse yourself in building an AI project from scratch. Theme: Create something remarkable using AI—whether it’s AI x AR, AI x Web3, or any other exciting combination. Global Collaboration: Join teams from around the world—Vancouver, London, and beyond. Mentorship: Get support from experienced mentors as you develop your MVP (Minimum Viable Product). Demo Day: Showcase your creation, pitch your vision, and potentially change your life. 🎉 Beeloud Style: Expect to meet new people, exchange ideas, and collaborate. Be open, be curious, and be ready to innovate! 🔁 Repost this post to spread the word! Let’s make BuildAI 2024 a huge success. 🚀 See you there! 🎓🌍 #BuilAI2024 #AIInnovation #Hackathon #Beeloud

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Impressive! It can tackle math problems, aid in interview preparation, provide real-time translations, sing songs, scan and explain surroundings, assist visually impaired individuals in understanding their environment, and much more. OpenAI GPT-4o is transforming human-computer interaction! It seamlessly processes text, audio, and images with lightning-fast responses. With enhanced language comprehension and multi-modal understanding, it's a game-changer for natural interactions. #ai #gpt4o #llm #datascience #machinelearning #deeplearning #openai #genai

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Computer Science vs Software Engineering, Science vs Engineering How Artificial Intelligence affects them The following is a letter I wrote to my son who studies Math and CS at University of Toronto now. Hi xxx, Nowadays, as the scope of artificial intelligence becomes wider and wider, many engineering fields such as software engineering will be largely replaced by artificial intelligence-based computer programs and robots (a holistic system). Personally, I'm glad you're lucky enough to study computer science instead of software engineering. Because I think software engineering is a dark field after four years you graduate from the University of Toronto. Software engineering began in 1993, when a group of people with CS backgrounds wanted to quickly apply CS research results to solve customers' problems in computer technology, mainly computer programs (software). Software engineering defines software development life cycle, framework and other standards in an engineering way, and has very specific rules for what to do under what circumstances and what kind of problems to solve. It largely increases the efficiency of creating a solution for a client's business problems. And let the people in different fields of software engineering have interchangeable understandings and knowledge.   This doesn't apply to science, just like physicists don't know much and have a hard time understanding biology. Thus, it brings about a glorious and admirable period of software engineering to date. However, the big difference between Science and Engineering is that  Science relies heavily on creative thinking, just like art, and humans still simply don't understand this. Christianity believes that this is grace from God to certain people. Engineering is very good at transferring the results of Science into its own fields. Please do not hesitate to ask me questions if you don't understand about this. Lovingly yours, Dad

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