diff --git a/.history/index_20240713160047.html b/.history/index_20240713160047.html new file mode 100644 index 0000000..6242781 --- /dev/null +++ b/.history/index_20240713160047.html @@ -0,0 +1,189 @@ + + + + + + + CoreRec-e + + + + + + + + + + + + + + +
+
+
+
+
CoreRec
+ +
+
+
+
+

CoreRec is your all-in-one recommendation engine for graph-based algorithms.

+

CoreRec excels in node recommendations, model training, and graph visualizations, + making it the ultimate tool for data scientists and researchers.

+ + + Contribute + +
+
+
+
+
+
+
+
+
+
+ 
import core_rec as cr
+import vish_graphs as vg
+import numpy as np
+
+
+file_path=vg.generaterandom_graph(100,seed=221)
+graph_dataset = cs.GraphDataset(adj_matrix)
+data_loader = DataLoader(graph_dataset, batch_size=5, shuffle=True)
+adj_matrix = np.loadtxt(file_path,delimiter=',')
+model = cs.GraphTransformer(
+           num_layers, d_model, num_heads, d_feedforward, input_dim)
+           top_nodes = vg.find_top_nodes(adj_matrix, num_nodes=5)
+
+num_epochs = 10
+cs.train_model(model, data_loader, criterion, optimizer, num_epochs)
+       
+       
+node_index = 2   #target node
+recommended_nodes = cs.predict(model, adj_matrix, node_index, top_k=5, threshold=0.5)
+print(f"Recommended nodes for node {node_index}: {recommended_nodes}")
+
+
+
+
+
+
+ + +
+
+
+
+

Reasons Why People Will Love CoreRec

+
+
+
+
+
+ +
+
+
+ Dead Simple +
+
+
+
+
+
+
+ +
+
+
+ Highly Intuitive +
+
+
+
+
+
+
+ +
+
+
+ Light as a Feather +
+
+
+
+
+
+
+ +
+
+
+ Blazing Fast +
+
+
+
+
+
+
+ +
+
+
+ Extensible +
+
+
+
+
+
+ +
+
+
+ Easy Styling +
+
+
+
+
+
+
+
+ + + + + + + + + + + + + + diff --git a/.history/index_20240713160050.html b/.history/index_20240713160050.html new file mode 100644 index 0000000..723b5c5 --- /dev/null +++ b/.history/index_20240713160050.html @@ -0,0 +1,189 @@ + + + + + + + CoreRec-easy to use, fast, and efficient graph-based recommendation engine + + + + + + + + + + + + + + +
+
+
+
+
CoreRec
+ +
+
+
+
+

CoreRec is your all-in-one recommendation engine for graph-based algorithms.

+

CoreRec excels in node recommendations, model training, and graph visualizations, + making it the ultimate tool for data scientists and researchers.

+ + + Contribute + +
+
+
+
+
+
+
+
+
+
+ 
import core_rec as cr
+import vish_graphs as vg
+import numpy as np
+
+
+file_path=vg.generaterandom_graph(100,seed=221)
+graph_dataset = cs.GraphDataset(adj_matrix)
+data_loader = DataLoader(graph_dataset, batch_size=5, shuffle=True)
+adj_matrix = np.loadtxt(file_path,delimiter=',')
+model = cs.GraphTransformer(
+           num_layers, d_model, num_heads, d_feedforward, input_dim)
+           top_nodes = vg.find_top_nodes(adj_matrix, num_nodes=5)
+
+num_epochs = 10
+cs.train_model(model, data_loader, criterion, optimizer, num_epochs)
+       
+       
+node_index = 2   #target node
+recommended_nodes = cs.predict(model, adj_matrix, node_index, top_k=5, threshold=0.5)
+print(f"Recommended nodes for node {node_index}: {recommended_nodes}")
+
+
+
+
+
+
+ + +
+
+
+
+

Reasons Why People Will Love CoreRec

+
+
+
+
+
+ +
+
+
+ Dead Simple +
+
+
+
+
+
+
+ +
+
+
+ Highly Intuitive +
+
+
+
+
+
+
+ +
+
+
+ Light as a Feather +
+
+
+
+
+
+
+ +
+
+
+ Blazing Fast +
+
+
+
+
+
+
+ +
+
+
+ Extensible +
+
+
+
+
+
+ +
+
+
+ Easy Styling +
+
+
+
+
+
+
+
+ + + + + + + + + + + + + + diff --git a/.history/index_20240713160053.html b/.history/index_20240713160053.html new file mode 100644 index 0000000..867e513 --- /dev/null +++ b/.history/index_20240713160053.html @@ -0,0 +1,189 @@ + + + + + + + CoreRec-asy to use, fast, and efficient graph-based recommendation engine + + + + + + + + + + + + + + +
+
+
+
+
CoreRec
+ +
+
+
+
+

CoreRec is your all-in-one recommendation engine for graph-based algorithms.

+

CoreRec excels in node recommendations, model training, and graph visualizations, + making it the ultimate tool for data scientists and researchers.

+ + + Contribute + +
+
+
+
+
+
+
+
+
+
+ 
import core_rec as cr
+import vish_graphs as vg
+import numpy as np
+
+
+file_path=vg.generaterandom_graph(100,seed=221)
+graph_dataset = cs.GraphDataset(adj_matrix)
+data_loader = DataLoader(graph_dataset, batch_size=5, shuffle=True)
+adj_matrix = np.loadtxt(file_path,delimiter=',')
+model = cs.GraphTransformer(
+           num_layers, d_model, num_heads, d_feedforward, input_dim)
+           top_nodes = vg.find_top_nodes(adj_matrix, num_nodes=5)
+
+num_epochs = 10
+cs.train_model(model, data_loader, criterion, optimizer, num_epochs)
+       
+       
+node_index = 2   #target node
+recommended_nodes = cs.predict(model, adj_matrix, node_index, top_k=5, threshold=0.5)
+print(f"Recommended nodes for node {node_index}: {recommended_nodes}")
+
+
+
+
+
+
+ + +
+
+
+
+

Reasons Why People Will Love CoreRec

+
+
+
+
+
+ +
+
+
+ Dead Simple +
+
+
+
+
+
+
+ +
+
+
+ Highly Intuitive +
+
+
+
+
+
+
+ +
+
+
+ Light as a Feather +
+
+
+
+
+
+
+ +
+
+
+ Blazing Fast +
+
+
+
+
+
+
+ +
+
+
+ Extensible +
+
+
+
+
+
+ +
+
+
+ Easy Styling +
+
+
+
+
+
+
+
+ + + + + + + + + + + + + + diff --git a/.history/index_20240713160054.html b/.history/index_20240713160054.html new file mode 100644 index 0000000..f45ae10 --- /dev/null +++ b/.history/index_20240713160054.html @@ -0,0 +1,189 @@ + + + + + + + CoreRec-Easy to use, fast, and efficient graph-based recommendation engine + + + + + + + + + + + + + + +
+
+
+
+
CoreRec
+ +
+
+
+
+

CoreRec is your all-in-one recommendation engine for graph-based algorithms.

+

CoreRec excels in node recommendations, model training, and graph visualizations, + making it the ultimate tool for data scientists and researchers.

+ + + Contribute + +
+
+
+
+
+
+
+
+
+
+ 
import core_rec as cr
+import vish_graphs as vg
+import numpy as np
+
+
+file_path=vg.generaterandom_graph(100,seed=221)
+graph_dataset = cs.GraphDataset(adj_matrix)
+data_loader = DataLoader(graph_dataset, batch_size=5, shuffle=True)
+adj_matrix = np.loadtxt(file_path,delimiter=',')
+model = cs.GraphTransformer(
+           num_layers, d_model, num_heads, d_feedforward, input_dim)
+           top_nodes = vg.find_top_nodes(adj_matrix, num_nodes=5)
+
+num_epochs = 10
+cs.train_model(model, data_loader, criterion, optimizer, num_epochs)
+       
+       
+node_index = 2   #target node
+recommended_nodes = cs.predict(model, adj_matrix, node_index, top_k=5, threshold=0.5)
+print(f"Recommended nodes for node {node_index}: {recommended_nodes}")
+
+
+
+
+
+
+ + +
+
+
+
+

Reasons Why People Will Love CoreRec

+
+
+
+
+
+ +
+
+
+ Dead Simple +
+
+
+
+
+
+
+ +
+
+
+ Highly Intuitive +
+
+
+
+
+
+
+ +
+
+
+ Light as a Feather +
+
+
+
+
+
+
+ +
+
+
+ Blazing Fast +
+
+
+
+
+
+
+ +
+
+
+ Extensible +
+
+
+
+
+
+ +
+
+
+ Easy Styling +
+
+
+
+
+
+
+
+ + + + + + + + + + + + + + diff --git a/.history/index_20240713160056.html b/.history/index_20240713160056.html new file mode 100644 index 0000000..8bbb442 --- /dev/null +++ b/.history/index_20240713160056.html @@ -0,0 +1,189 @@ + + + + + + + CoreRec : Easy to use, fast, and efficient graph-based recommendation engine + + + + + + + + + + + + + + +
+
+
+
+
CoreRec
+ +
+
+
+
+

CoreRec is your all-in-one recommendation engine for graph-based algorithms.

+

CoreRec excels in node recommendations, model training, and graph visualizations, + making it the ultimate tool for data scientists and researchers.

+ + + Contribute + +
+
+
+
+
+
+
+
+
+
+ 
import core_rec as cr
+import vish_graphs as vg
+import numpy as np
+
+
+file_path=vg.generaterandom_graph(100,seed=221)
+graph_dataset = cs.GraphDataset(adj_matrix)
+data_loader = DataLoader(graph_dataset, batch_size=5, shuffle=True)
+adj_matrix = np.loadtxt(file_path,delimiter=',')
+model = cs.GraphTransformer(
+           num_layers, d_model, num_heads, d_feedforward, input_dim)
+           top_nodes = vg.find_top_nodes(adj_matrix, num_nodes=5)
+
+num_epochs = 10
+cs.train_model(model, data_loader, criterion, optimizer, num_epochs)
+       
+       
+node_index = 2   #target node
+recommended_nodes = cs.predict(model, adj_matrix, node_index, top_k=5, threshold=0.5)
+print(f"Recommended nodes for node {node_index}: {recommended_nodes}")
+
+
+
+
+
+
+ + +
+
+
+
+

Reasons Why People Will Love CoreRec

+
+
+
+
+
+ +
+
+
+ Dead Simple +
+
+
+
+
+
+
+ +
+
+
+ Highly Intuitive +
+
+
+
+
+
+
+ +
+
+
+ Light as a Feather +
+
+
+
+
+
+
+ +
+
+
+ Blazing Fast +
+
+
+
+
+
+
+ +
+
+
+ Extensible +
+
+
+
+
+
+ +
+
+
+ Easy Styling +
+
+
+
+
+
+
+
+ + + + + + + + + + + + + + diff --git a/.history/index_20240713160058.html b/.history/index_20240713160058.html new file mode 100644 index 0000000..e9444b5 --- /dev/null +++ b/.history/index_20240713160058.html @@ -0,0 +1,189 @@ + + + + + + + CoreRec : Easy to use, fast, and efficient graph-based recommendation engine + + + + + + + + + + + + + + +
+
+
+
+
CoreRec
+ +
+
+
+
+

CoreRec is your all-in-one recommendation engine for graph-based algorithms.

+

CoreRec excels in node recommendations, model training, and graph visualizations, + making it the ultimate tool for data scientists and researchers.

+ + + Contribute + +
+
+
+
+
+
+
+
+
+
+ 
import core_rec as cr
+import vish_graphs as vg
+import numpy as np
+
+
+file_path=vg.generaterandom_graph(100,seed=221)
+graph_dataset = cs.GraphDataset(adj_matrix)
+data_loader = DataLoader(graph_dataset, batch_size=5, shuffle=True)
+adj_matrix = np.loadtxt(file_path,delimiter=',')
+model = cs.GraphTransformer(
+           num_layers, d_model, num_heads, d_feedforward, input_dim)
+           top_nodes = vg.find_top_nodes(adj_matrix, num_nodes=5)
+
+num_epochs = 10
+cs.train_model(model, data_loader, criterion, optimizer, num_epochs)
+       
+       
+node_index = 2   #target node
+recommended_nodes = cs.predict(model, adj_matrix, node_index, top_k=5, threshold=0.5)
+print(f"Recommended nodes for node {node_index}: {recommended_nodes}")
+
+
+
+
+
+
+ + +
+
+
+
+

Reasons Why People Will Love CoreRec

+
+
+
+
+
+ +
+
+
+ Dead Simple +
+
+
+
+
+
+
+ +
+
+
+ Highly Intuitive +
+
+
+
+
+
+
+ +
+
+
+ Light as a Feather +
+
+
+
+
+
+
+ +
+
+
+ Blazing Fast +
+
+
+
+
+
+
+ +
+
+
+ Extensible +
+
+
+
+
+
+ +
+
+
+ Easy Styling +
+
+
+
+
+
+
+
+ + + + + + + + + + + + + + diff --git a/index.html b/index.html index 8f350f5..e9444b5 100644 --- a/index.html +++ b/index.html @@ -4,8 +4,8 @@ - Prism - Bootstrap 4 Open Source Landing Page Template - + CoreRec : Easy to use, fast, and efficient graph-based recommendation engine +