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DeepMind’s AlphaProof and AlphaGeometry 2 have just shown how AI can compete at the highest level of mathematics – solving complex problems and earning points equivalent to a silver medal in the International Mathematical Olympiad (IMO). Self-training, reinforcement learning, and critical thinking skills enable AI to solve advanced math problems. How can these capabilities be applied to help your business? Subscribe to our AI newsletter to find out. 📬 Sign up here 👉 https://lnkd.in/d9GMGzWN #AIBytes #Innovation #SoftwareDevelopment #AI  

AI Breakthrough: Google DeepMind Tackles Complex Math! 🤖✨ TL;DR: Google DeepMind has unveiled AlphaProof and AlphaGeometry 2, pioneering AI systems that are now effectively solving challenging math problems. Achieving a remarkable success rate at the International Mathematical Olympiad, this milestone showcases the evolving reasoning capabilities of AI. Highlights: • Groundbreaking AI: Introduction of AlphaProof and AlphaGeometry 2. • Olympiad Achievement: 4 out of 6 problems solved, earning silver medal status. • Historical Milestone: First AI recognition in a math competition! • Overcoming Challenges: Tackling logical reasoning and abstract thinking. • Data Solutions: Reinforcement learning bridges gaps in formal math training. • Future Potential: Open doors for collaboration between AI and human mathematicians. #AIRevolution #DeepMind #Mathematics #Innovation #TechTrends Article Source: https://lnkd.in/g-eveKVX

I recently had the privilege of completing the "Specialization in Machine Learning" from Stanford University and DeepLearning.AI. This intensive 8-9 week program provided a comprehensive foundation in AI and machine learning, equipping me with valuable knowledge and skills. 🚀 Key Courses Completed: Supervised Machine Learning: Regression and Classification Advanced Learning Algorithms Unsupervised Learning, Recommenders, and Reinforcement Learning Special thanks to Andrew Ng for his exceptional teaching approach, making these complex concepts accessible and engaging. 👏 Looking forward to leveraging these skills in AI-driven innovation. #AI #MachineLearning #ContinuousLearning #Innovation #CareerDevelopment 🌟

I am thrilled to share that I recently attended an enlightening online workshop on Machine Learning, conducted by the prestigious National Institute of Technology (NIT), Kurukshetra. The workshop was an incredible experience, filled with rich insights and hands-on learning. It covered a range of topics, from foundational concepts to advanced techniques. Key highlights of the workshop included: In-depth sessions on algorithms and models: We delved into supervised and unsupervised learning, reinforcement learning, and neural networks. Expert speakers and mentors: Learning from some of the best minds in the field of machine learning and data science. Interactive Q&A sessions: Getting personalized feedback and advice, which helped in clarifying complex concepts. A huge thank you to the organizers and instructors at NIT Kurukshetra for putting together such a comprehensive and engaging workshop. It was a fantastic opportunity to enhance my skills and network with professionals and peers passionate about machine learning. I am looking forward to applying the knowledge and skills gained to my projects and exploring further in this dynamic field. #MachineLearning #DataScience #NITKurukshetra #ContinuousLearning #ProfessionalDevelopment #AI

Math is the building block of machine learning; it is founded on four major areas which enables the use of algorithms: Algebra, Calculus, Probability and Statistics. Below is a quick look at each: Linear Algebra: The foundation for data structures, used to manage and manipulate high dimensional data. Calculus: Deals with change and helps in optimising algorithms for better learning from data. Probability & Statistics: These two fields are the basis of decision making thereby facilitating predictions as well as inference from data. I will post my weekly notes here so follow along if you want more in-depth explanations about mathematical concepts behind machine learning! Artificial Intelligence, Generative AI, Machine Learning #ArtificialIntelligence #MachineLearning #EducationTechnology #EdTech #LifelongLearning #StudyNotes #DigitalLearning #AI #ML #LinkedInLearning #ProfessionalDevelopment #PersonalBranding #CareerGrowth #LearningAndDevelopment #SkillUp

🎉 Thrilled to share that I successfully defended my Master's thesis last week! 🎓 Title: Enhancing Poor-Quality Datasets with Knowledge Graph Embeddings for Machine Learning My research focused on improving machine learning models by integrating knowledge graph embeddings into datasets with limited or poorly correlated features. This study investigates the impact of knowledge graph embeddings on classification and regression tasks. This work highlights the potential of using knowledge graphs to boost the performance of machine learning models, paving the way for future advancements in this area. A special thank you to my supervisor Anna Queralt for her constant support and invaluable feedback throughout this thesis. Her guidance was essential to the success of this work. #MachineLearning #KnowledgeGraphs #DataScience #Research #MastersThesis #AI

✖ ➕ ➗ Unlock the full potential of AI: Revisit the math basics and transform your AI journey! I often repeat this mantra: To dive into AI, start with the fundamentals, and that means Math. So, do you need math to dabble in AI? Not necessarily. But to truly excel? Absolutely. Whether you're about to embark on your AI adventure or you're already on the path, my advice is to revisit those university notebooks. Dive back into calculus, algebra, and statistics. Refreshing your grasp on these core subjects will significantly elevate your AI game. #ai #genai #maths

🌟 Ever thought about how AI works its magic? Picture this: a self-driving car cruising through the city, recognizing signs and avoiding pedestrians. All thanks to math! My new article, "Mastering AI Fundamentals: Importance of Linear Algebra" explains how math, especially linear algebra, is the key to AI. Learn how math shapes AI and find a beginner-friendly learning path with references. Whether you're just starting out in AI or have some experience, this article is your guide to understanding the math that powers AI. Link in the comments section. #ai #machinelearning #linearalgebra #mathinai #geogo

The Math Behind Machine Learning: A Practical Guide Mathematics is the backbone of machine learning. Every model, every algorithm, is built on mathematical concepts that drive predictions and insights. Understanding the math behind these models isn't just helpful—it's essential for truly mastering machine learning. Today, I'm sharing a comprehensive PDF on Mathematics for Machine Learning, complete with practical implementations. It's a valuable resource for anyone looking to deepen their understanding of how math underpins the world of ML. #MachineLearning #Mathematics #DataScience #AI #ML

I'm excited to share that I've completed a 6-week Machine Learning Workshop! Through this intensive program, I gained hands-on experience in machine learning fundamentals, collaborative problem-solving, and practical implementation of ML concepts. Looking forward to applying these skills in future projects and continuing to grow in the field of AI and machine learning. I just want to thank my instructor Bevan Deniz Çılğın for his guidance. His expertise and passion definitely made this workshop truly transformative. Also, huge thanks to Hacettepe Üniversitesi Yapay Zeka Topluluğu for organizing such a great workshop. #MachineLearning #AI #ContinuousLearning #ML