Results for “networks”

Build and train graph neural networks for drug discovery, protein modeling, and molecular science using PyTorch-native tools.

Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing topologies — applicable to social, biological, transportation, citation, and any pairwise-relationship networks. This is classical graph analytics, not deep learning — for training graph neural networks (GCN/message passing, node/edge/graph classification on Cora-style data) use alterlab-torch-geometric instead. Part of the AlterLab Academic Skills suite.

PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production

Build and train graph neural networks with PyTorch Geometric, covering node/link/graph classification, message passing layers, heterogeneous graphs, and custom datasets.

Assess and implement the CISA Zero Trust Maturity Model v2.0 across identity, devices, networks, applications, and data pillars to achieve progressive zero trust maturity.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

Produces NetworkX code with explicit graph kind, node identity, edge multiplicity, direction, attribute schema, weight semantics, and algorithm preconditions, including testing.

Create, manipulate, and analyze complex networks and graphs using the NetworkX Python package, including algorithms, generators, I/O, and visualization.

Implements Kubernetes network policies for micro-segmentation, covering ingress/egress rules, Calico and Cilium, with a Python CLI for managing and validating policies.

Configures and troubleshoots network infrastructure: DNS records, reverse proxies, SSL certificates, firewalls, CDNs, and load balancers.

Create, analyze, and visualize complex networks and graphs in Python with NetworkX, including graph algorithms, community detection, synthetic network generation, and multiple I/O formats.

Expert network engineer specializing in modern cloud networking, security architectures, and performance optimization. Masters multi-cloud connectivity, service mesh, zero-trust networking, SSL/TLS, global load balancing, and advanced troubleshooting. Handles CDN optimization, network automation, and compliance. Use PROACTIVELY for network design, connectivity issues, or performance optimization.

Networking Outreach

Create, manipulate, and analyze complex networks and graphs using the NetworkX Python package.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting...

Internal network assessment. VLAN hopping, ARP spoofing detection, broadcast protocol abuse (LLMNR/NBT-NS/mDNS), network segmentation verification, SNMP enumeration, NFS exposure, router/switch audit, and internal service mapping. Assumes attacker has network access. Uses nmap, arp-scan, nbtscan, snmpwalk, onesixtyone, smbmap, nfs-common, masscan, hping3, and netexec.

Build and maintain professional relationships through strategic outreach, events, and follow-up, with structured frameworks for deliberate practice.

Create and apply Kubernetes NetworkPolicies to enforce pod-level network segmentation, restrict traffic between pods and namespaces, and block access to cloud metadata endpoints.

Reads existing per-leader research files to map co-authorships, endorsements, and organizational ties across movement leaders, producing a cross-leader network graph with clusters, bridges, and isolates.

Create, manipulate, and analyze complex networks and graphs with the NetworkX Python package, covering graph construction, algorithms, generators, I/O, and visualization.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

Create, analyze, and visualize complex networks and graphs in Python, covering graph construction, algorithms, generators, I/O, and visualization.

ENet reliable UDP skill for channels and packet fragmentation.