Advanced Graph Analysis
CoreRec provides cutting-edge tools for analyzing complex graph structures, making it ideal for data scientists and researchers.
CoreRec offers a robust recommendation system based on graph analysis. It can recommend similar nodes within a graph, aiding in various applications such as personalized recommendations in social networks or product recommendations in e-commerce platforms.
CoreRec provides cutting-edge tools for analyzing complex graph structures, making it ideal for data scientists and researchers.
Utilize CoreRec's powerful engine to recommend similar nodes within a graph, enhancing user experience and engagement.
Define and train Transformer models tailored to your graph data with customizable parameters for optimal performance.
Seamlessly integrate graph data with PyTorch datasets, streamlining the model training process.
Train your models with ease using CoreRec's flexible training functions, supporting various configurations.
Measure the accuracy of your recommendations with robust metrics provided by CoreRec.
Create stunning 2D visualizations of your graphs, making data analysis more intuitive and insightful.
Experience your graphs in 3D with customizable features, providing a deeper understanding of complex networks.
CoreRec provides cutting-edge tools for analyzing complex graph structures. These tools are designed to help data scientists and researchers understand the intricate relationships within their data, enabling more informed decision-making and insights.
import core_rec as cr
graph = cr.load_graph("path/to/graph")
analysis_results = cr.analyze_graph(graph)
Utilize CoreRec's powerful engine to recommend similar nodes within a graph. This feature enhances user experience and engagement by providing personalized recommendations based on graph data.
import core_rec as cr
recommendations = cr.recommend_similar_nodes(graph, node_id)
Define and train Transformer models tailored to your graph data with customizable parameters. This allows for optimal performance in various graph-related tasks such as node classification or link prediction.
import core_rec as cr
model = cr.GraphTransformer(num_layers=2, d_model=128, num_heads=4, d_feedforward=512, input_dim=10)
Seamlessly integrate graph data with PyTorch datasets, streamlining the model training process. This feature simplifies the preparation of graph data for machine learning tasks.
import core_rec as cr
dataset = cr.GraphDataset(adj_matrix)
data_loader = DataLoader(dataset, batch_size=32, shuffle=True)
Train your models with ease using CoreRec's flexible training functions. These functions support various configurations, making it easier to adapt to different training requirements.
import core_rec as cr
cr.train_model(model, data_loader, criterion, optimizer, num_epochs=10)
Measure the accuracy of your recommendations with robust metrics provided by CoreRec. This feature ensures that your recommendation system is performing optimally.
import core_rec as cr
accuracy = cr.aaj_accuracy(graph, node_index, recommended_indices)
Create stunning 2D visualizations of your graphs, making data analysis more intuitive and insightful. This feature helps in better understanding the structure and relationships within the graph.
import vish_graphs as vg
vg.draw_graph(adj_matrix, nodes, top_nodes)
Experience your graphs in 3D with customizable features, providing a deeper understanding of complex networks. This feature is particularly useful for visualizing large and intricate graph structures.
import vish_graphs as vg
vg.draw_graph_3d(adj_matrix, nodes, top_nodes)
If your documentation is very long you can host the full docs page (including FAQ etc) on GitHub and provide a Call to Action button below to direct users there.
CoreRec and VishGraphs are completely open source projects. We highly support and encourage open source contributions. You are free to use, modify, and distribute the code as long as you adhere to the terms of the open source license.
[Tip for developers]: If you find this project useful, consider contributing back to the community by submitting bug fixes, feature enhancements, or documentation improvements.
If you want to support the development of these open source projects, you can star the repository on GitHub. Thank you for your support!
Discover the power of graph analysis and recommendation with CoreRec & VishGraphs. Dive into our comprehensive manual and explore the endless possibilities.
Feel free to get in touch if you have any questions or suggestions.