unstructured.io’s Post

🚀 New research, new challenges, and a lot of excitement! I’m thrilled to share our latest working paper: Automated Knowledge Concept Annotation and Question Representation Learning for Knowledge Tracing 📚 Here’s a quick, non-technical breakdown (because understanding research should be accessible to everyone!): 💡 What is Knowledge Tracing (KT)? Think about online learning platforms. When you solve exercises, KT models track how well you’re mastering a subject over time. 🤔 What’s the issue with current KT models? Imagine being a teacher who has no idea what the actual questions are, only working with numbers as “question IDs.” It’s like assessing learning without ever seeing the actual content – sounds strange, right? 🔧 What did we change? We gave KT models the power to actually understand the questions (finally!) and their associated concepts. The result? A significant performance boost for all KT models we tested. 💥 Curious about the details? 📄 Check out our preprint: https://lnkd.in/eAUhwAT6 Big thanks to my amazing supervisors Stefan Feuerriegel and Mrinmaya Sachan for their invaluable guidance on this fun journey! 🙏

As part of my ongoing journey in the Post Graduate Program in Artificial Intelligence and Machine Learning, I recently completed a capstone project that challenged and expanded my understanding of real-world applications of AI and ML. This hands-on experience allowed me to apply the concepts and tools I’ve learned to tackle complex business problems. 🔍 Key Learnings & Achievements: 1. Data Analysis & Feature Engineering: Gained deep insights into handling large datasets and performing data preprocessing, feature engineering, and data visualization to uncover hidden patterns. 2. Machine Learning Model Building: Successfully implemented various machine learning models, including supervised and unsupervised learning algorithms, to solve business challenges. 3. Business Problem Solving: Developed models to provide actionable insights for improving business operations, customer experience, and revenue generation. 4. Tools & Techniques: Worked extensively with Python, Pandas, NumPy and visualization libraries such as Seaborn and Matplotlib to interpret and communicate findings effectively. 💡 This project not only strengthened my technical expertise in AI & ML but also enhanced my problem-solving skills in developing business-oriented solutions. Looking forward to applying these skills to real-world challenges! Stay tuned for more updates as I continue my AI/ML journey! #ArtificialIntelligence #MachineLearning #DataScience #CapstoneProject #AIApplications #BusinessAnalytics #AIML

🤔 Did you know that when quizzes/tests are given WITHOUT feedback, retrieval practice enhances later retention more than restudying the material! 🚀 NEW BLOG 🟢 The Power of Retrieval Practice

🚀 Exciting News! 🚀 I'm thrilled to announce the successful completion of the "Recommendation Systems" course, a pivotal step in my journey towards mastering Data Science and Machine Learning with MIT Institute for Data, Systems, and Society (IDSS), thanks to Great Learning! Throughout this immersive learning experience, I've delved deep into the intricacies of building recommendation systems, culminating in the development of a cutting-edge project: "Building a recommendation system to recommend the best Amazon products to users." I invite you to check out my e-portfolio for more details. This project not only allowed me to apply the theoretical concepts learned in the course but also provided a hands-on opportunity to harness the power of data to deliver tailored recommendations. By leveraging advanced algorithms and techniques, I've gained valuable insights into user preferences, behavior patterns, and product affinity, ultimately enhancing user experience and driving engagement. Looking ahead, I am excited about the future prospects of utilizing this knowledge to build recommendation systems for various industries including banks, insurance, hospitals, and other data-driven organizations. My goal is to help these organizations optimize costs and increase profit based on recommendations for their customers I'm immensely grateful for the guidance and expertise provided by the instructors at MIT Institute for Data, Systems, and Society (IDSS) and Great Learning, whose dedication has been instrumental in shaping my understanding of recommendation systems and their real-world applications. As I embark on the next phase of my journey, I look forward to leveraging this newfound knowledge and skill set to tackle complex challenges and make meaningful contributions in the field of Data Science and Machine Learning. A heartfelt thank you to everyone who has supported me along the way. Here's to continuous learning, growth, and the pursuit of excellence! #DataScience #MachineLearning #RecommendationSystems #MITIDSS #ContinuousLearning #GreatLearning

🚀 Delighted to announce the release of our latest research paper, "Effecti-Net: A Multimodal Framework and Database for Educational Content Effectiveness Analysis," now accessible on ACM Digital Library! 📝 In this groundbreaking study, we tackle the challenge of evaluating the impact of educational video content on students. Our research introduces the innovative 'Effecti-Net' architecture, a sophisticated deep learning model integrating data from multiple sensor modalities such as EEG, Eye Tracker, GSR, and PPG. We leverage this model alongside the 'DECEP' dataset, a repository comprising 597 minutes of multimodal sensor data, to predict student-perceived content effectiveness. 🔗 Dive into the abstract and access the full paper here: https://lnkd.in/gw2TP964 🌟 Our research bridges the gap in understanding student responses to educational materials, offering educators and content creators a comprehensive framework to develop more engaging content. We achieved remarkable results, benchmarking our approach against conventional methods with a lowest MSE of 0.1651 and MAE of 0.3544 on the DECEP dataset. 💬 We invite you to explore our findings and share your insights. Your feedback is invaluable as we continue to innovate in educational content analysis. #ResearchPaper #EducationalTechnology #DeepLearning #DataAnalysis #ACMDigitalLibrary #Innovation #EducationResearch

🌟 Enhance Your Vocab Lessons with Pedagog.AI! 📚 Unveil the potential of our Vocab List Generator, the perfect tool for crafting custom vocabulary lists. Simply input your grade level, topic focus, and preferred language, and let Pedagog.AI work its magic. 🎩✨ 📖 Adjust and refine with your feedback, or export to Google Docs to personalize further. 🔗 Take your teaching to the next level! Click the link in our bio to sign up and access a world of free educational tools. #EdTech #VocabularyBuilder #TeacherTools

Gemma Sprint is a new program in the Google Machine Learning Bootcamp. Participants can propose ideas to fine-tune the Gemma model, distribute the model on Hugging Face, and create tutorial apps or code examples. I also fine-tuned the Gemma model to generate abstracts of papers based on short, summarized sentences on topics provided by users. It was my first attempt at fine-tuning an LLM model, so I didn't expect much. However, the results were better than I thought. I felt encouraged while tuning the model, writing code, and testing datasets. Below are the links to my results. [Hugging Face] : https://lnkd.in/g4iCvBJJ [Github repository] : https://lnkd.in/gRFPX3EX [Blog Post] : https://lnkd.in/g6eMYbTC #GemmaSprint

I am thrilled to share that my upcoming book chapter, titled "Impact of Information Technology on the Education System and Teaching Process," is now available for pre-booking! https://lnkd.in/gQtj9gfx

🚨 Are Your Students Struggling to Stay Engaged? 🚨 Many students are bypassing traditional reading for quick internet searches to get through their courses. But are they really mastering the material this way? With rising costs, lack of engagement, and a growing disconnect from textbooks, it’s no wonder many aren’t passing courses on the first try. To support students we’re offering eBook rentals to make learning more affordable, and interactive features to go beyond just reading or note-taking, students can now engage with the content on a deeper level with real-time practice tools including AI support in many of our titles. Pearson is focusing on a full digital learning experience designed to bridge the learing gap. It's not just about reading—it's about engaging with the material and preparing students for success from the start. Are your students truly prepared to excel? Let's catch up this semester to see how we can support your efforts. https://lnkd.in/dTkdc7PK #DigitalLearning #StudentSuccess #EdTech #InteractiveLearning #GoDigital

Note-taking is a crucial skill for every academic. But most don't use the right tool. The tool I am talking about is Obsidian. It is a complete tool for all academic note-taking and reference management needs. It just takes notes, but: 1. Notes are globally searchable 2. Notes include PDFs and images 3. Notes are connected with links like websites 4. Plugins allow to you add calendars, kanbans, checklists to your notes Obsidian is like the Google of notes, providing a centralized platform for organizing and accessing information. It's the tool that keeps everything together, giving you the control over the right information in seconds. Want to learn some Obsidian magic, follow the link in this post. Also check out the pinned post for my newest webinar, where you can learn how to get started with academic note-taking. It starts in just a few days https://lnkd.in/edsF3YFQ