Many powerful Machine Learning algorithms are based on graphs, e.g., Page Rank (Pregel), Recommendation Engines (collaborative filtering), text summarization, and other NLP tasks. Also, the recent developments with Graph Neural Networks connect the worlds of Graphs and Machine Learning even further.
Considering data pre-processing and feature engineering which are both vital tasks in Machine Learning Pipelines extends this relationship across the entire ecosystem. In this session, we will investigate the entire range of Graphs and Machine Learning with many practical exercises.
Connect with us:
Website:
Facebook:
Twitter:
LinkedIn:
Instagram:
21 view
13
4
4 years ago 00:27:28 21
Graph-Powered Machine Learning
4 years ago 00:40:19 3
CS224W: Machine Learning with Graphs | 2021 | Lecture 8.2 - Training Graph Neural Networks
2 years ago 00:20:27 3
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.2 - Applications of Graph ML
5 years ago 00:24:35 1
Big Data LDN 2019: Multi-model powered Machine Learning
5 years ago 00:46:45 1
Adding Graphs to Machine Learning
4 years ago 00:31:52 3
CS224W: Machine Learning with Graphs | 2021 | Lecture 9.2 - Designing the Most Powerful GNNs
4 years ago 00:48:37 3
Foundations of Data Science - Representation and Learning in Graph Neural Networks
9 years ago 00:01:53 13
A Graph of a Mathematical Function poem
1 year ago 00:59:46 1
Understanding Oversmoothing in Graph Neural Networks (GNNs): Insights from Two Theoretical Studies
9 months ago 00:40:08 1
The Most Important Algorithm in Machine Learning
1 year ago 00:10:05 1
Дом трансформер.
5 years ago 00:05:12 4
Neural Structured Learning - Part 2: Training with natural graphs
4 years ago 00:43:26 6
Keynote - Deep learning on graphs: successes, challenges, and next steps
2 years ago 00:41:48 6
“ ATOMS FOR PEACE “ SOVIET UNION ATOMIC RESEARCH PROPAGANDA FILM NUCLEAR POWER & RADIATION 30474a
2 years ago 00:29:51 1
“ ATOMS FOR PEACE “ SOVIET UNION ATOMIC RESEARCH PROPAGANDA FILM NUCLEAR POWER REEL 2 30474b
3 years ago 01:00:17 12
Topological Methods for Deep Learning
4 years ago 00:57:26 12
Reinforcement Learning for Hardware Design feat. Anna Goldie | Stanford MLSys Seminar Episode 14
3 years ago 00:20:40 6
Vector Search through Wikidata with Weaviate
3 years ago 01:40:55 3
#9 Working on Tensorflow Image Classification with Transfer Learning - ML Experiments
3 years ago 01:08:06 1
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs