W10_L10.8: Tutorial: node embeddings - part 1

Welcome to Week 10 Lecture 10 Part 8 of the course "Big Data and Biological Networks" by Dr. Nirav P Bhatt , Karthik Raman , Prof. Himanshu Sinha. Full Course: https://study.iitm.ac.in/ds/course_pages/BSBT4002.html Video Overview This tutorial provides a practical guide to implementing node embedding methods for graph data using Python, specifically focusing on applications in biological networks and big data. The video covers both matrix factorization-based and random walk-based node embedding techniques, explaining their theory, implementation, and practical relevance. These methods are then demonstrated on a real-world dataset, the human disease network, to showcase meaningful biological applications. The tutorial makes use of Python libraries such as NetworkX, NumPy, SciPy, Gensim, Karate Club, matplotlib, and scikit-learn to handle graph processing, mathematical computations, visualization, and machine learning tasks. For more details, visit: https://study.iitm.ac.in/ds/course_pages/BSBT4002.html Nirav Bhatt Associate Professor, Department of Data Science and AI, Wadhwani School of Data Science and AI Indian Institute of Technology Madras GitHub: https://github.com/bisect-group About IIT Madras' online Bachelor of Science programme IIT Madras offers four year BS programmes that aim to provide quality education to all, irrespective of age, educational background, or location. The BS programme has multiple levels, which provide flexibility to students to exit at any of these levels. Depending on the courses completed and credits earned, the learner can receive a Foundation Certificate from IITM CODE (Centre for Outreach and Digital Education), Diploma(s) from IIT Madras, or BSc/BS Degrees from IIT Madras. For more details, Visit: https://www.iitm.ac.in/academics/study-at-iitm/non-campus-bs-programmes #NodeEmbeddings #GraphLearning #HumanDiseaseNetwork #PythonTutorial #Bioinformatics #BigDataAndBiology #BiologicalNetworks #IITMadras #BSProgramme #DataScienceAI