Generative AI [2026 Updated] | Generative AI For Beginners | Simplilearn - Machine Learning With Graphs | How Machine Learning Uses Graphs | GNN For Beginners | Simplilearn

🔥Professional Certificate Course in Generative AI and Machine Learning - https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=WDT52cWmhsI&utm_medium=DescriptionFirstFold&utm_source=Youtube ️🔥 Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=WDT52cWmhsI&utm_medium=DescriptionFirstFold&utm_source=Youtube 🔥Professional Certificate Program in Generative AI and Machine Learning - IITG (India Only) - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=WDT52cWmhsI&utm_medium=DescriptionFirstFold&utm_source=Youtube 🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=WDT52cWmhsI&utm_medium=DescriptionFirstFold&utm_source=Youtube In this video, we’ll take a deep dive into the world of graphs in machine learning. We’ll start by breaking down what graphs are and explore their key components, including nodes, edges, and how they help represent relationships between data points. Then will see why graphs are essential in capturing complex relationships and structures that are often overlooked in traditional data representations. Next, we’ll look at the practical applications of graphs in machine learning . We’ll then discuss how to choose the right graph representation, such as adjacency matrices, adjacency lists, and edge lists, to best suit your data and task. We’ll dive into node embeddings and examine powerful techniques which allow us to learn meaningful features from graph-structured data. Finally, we’ll explore key graph algorithms such as PageRank, graph traversal methods, and graph-based clustering, and how these can be used to extract valuable insights from large-scale networks. 00:00:04 - Introduction 00:03:35 - What is a Graph? 00:05:36 - Why this is Useful? 00:07:31 - Real World Applications 00:10:16 - Machine Learning with Graphs 00:20:35 - Adjacency Matrix 00:23:40 - Adjacency List 00:25:00 - Edge List 00:26:10 - Choosing the Right Graph Representation 00:27:00 - What are Node Embeddings? 00:28:16 - DeepWalk 00:29:10 - Node2Vec 00:30:43 - Graph Convolutional Network 00:34:11 - PageRank 00:38:32 - Difference between BFS and DFS 00:38:51 - Graph Based Clustering ⏩ Check out More AI and ML Videos By Simplilearn: https://www.youtube.com/playlist?list=PLEiEAq2VkUULyr_ftxpHB6DumOq1Zz2hq #ai #machinelearning #gnn #cnn #neuralnetworks #gnn #graph #genai #generativeai #simplilearn #2025 ➡️ About the Professional Certificate Course in Generative AI and Machine Learning The Generative AI and Machine Learning course enriches your career with comprehensive coverage of machine learning, deep learning, NLP, generative AI, reinforcement learning, computer vision, and more. Combining theory with hands-on practice, it features live virtual sessions, projects with integrated labs, and masterclasses by eminent IIT Kanpur faculty. Key Features: ✅ Program completion certificate from E&ICT Academy, IIT Kanpur ✅ Simplilearn's JobAssist helps you get noticed by top hiring companies ✅ Curriculum delivered in live virtual classroom sessions by seasoned industry experts ✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering ✅ Interactive live-virtual masterclasses presented by esteemed IIT Kanpur faculty ✅ Practical learning through 15+ hands-on projects and industry relevant tools ✅ Access to a wide array of AI tools such as ChatGPT, DALL-E 2, TensorFlow, Keras, and more ✅ Earn official trophy and badges for ‘Microsoft Azure AI Fundamentals’ on the Microsoft Learn portal Skills Covered: ✅ Generative AI ✅ Prompt Engineering ✅ Large Language Models ✅ Generative AI Architectures ✅ Generative AI Models ✅ Machine Learning Algorithms ✅ Model Training and Optimization ✅ Ensemble Methods ✅ Deep Learning ✅ Natural Language Processing ✅ Computer Vision ✅ Reinforcement Learning ✅ Speech Recognition ✅ Supervised and Unsupervised Learning ✅ Model Evaluation and Validation Learning Path: ✅ IITK AIML - Program Induction ✅ IITK AIML - Programming Refresher ✅ IITK AIML - Applied Data Science with Python ✅ IITK AIML - Machine Learning ✅ IITK AIML - Deep Learning with Keras and TensorFlow ✅ IITK AIML - Essentials of GenAI, Prompt Engineering & ChatGPT ✅ IITK AIML - Advanced Generative AI ✅ IITK AIML - Capstone Electives: ✅ IITK AIML - ADL & Computer Vision ✅ IITK AIML - NLP and Speech Recognition ✅ IITK AIML - Reinforcement Learning ✅ IITK AIML - Microsoft Azure AI Fundamentals ✅ IITK AIML - Academic Masterclass by IIT Kanpur 👉 Learn More At: https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=WDT52cWmhsI&utm_medium=Description&utm_source=Youtube 🔥🔥