#go #anonymization #application_server #ccpa #compliance #data_anonymization #database #encryption #gdpr #gdpr_requirements #golang #legaltech #passportjs #pii #piidata #privacy #privacy_by_design #security #tokenization #user_consent #vault
https://github.com/securitybunker/databunker
https://github.com/securitybunker/databunker
GitHub
GitHub - securitybunker/databunker: Secure Vault for Customer PII/PHI/PCI/KYC Records
Secure Vault for Customer PII/PHI/PCI/KYC Records. Contribute to securitybunker/databunker development by creating an account on GitHub.
#typescript #compliance #data_anonymization #devsecops #gdpr #hardening #immutable_database #pci_dss #privacy_by_design #security #soc2 #tokenization #web_security #zero_trust
https://github.com/lunasec-io/lunasec
https://github.com/lunasec-io/lunasec
GitHub
GitHub - lunasec-io/lunasec: LunaSec - Dependency Security Scanner that automatically notifies you about vulnerabilities like Log4Shell…
LunaSec - Dependency Security Scanner that automatically notifies you about vulnerabilities like Log4Shell or node-ipc in your Pull Requests and Builds. Protect yourself in 30 seconds with the Luna...
#python #ai #artificial_intelligence #cython #data_science #deep_learning #entity_linking #machine_learning #named_entity_recognition #natural_language_processing #neural_network #neural_networks #nlp #nlp_library #python #spacy #text_classification #tokenization
spaCy is a powerful tool for understanding and processing human language. It helps computers analyze text by breaking it into parts like words, sentences, and entities (like names or places). This makes it useful for tasks such as identifying who is doing what in a sentence or finding specific information from large texts. Using spaCy can save time and improve accuracy compared to manual analysis. It supports many languages and integrates well with advanced models like BERT, making it ideal for real-world applications.
https://github.com/explosion/spaCy
spaCy is a powerful tool for understanding and processing human language. It helps computers analyze text by breaking it into parts like words, sentences, and entities (like names or places). This makes it useful for tasks such as identifying who is doing what in a sentence or finding specific information from large texts. Using spaCy can save time and improve accuracy compared to manual analysis. It supports many languages and integrates well with advanced models like BERT, making it ideal for real-world applications.
https://github.com/explosion/spaCy
GitHub
GitHub - explosion/spaCy: 💫 Industrial-strength Natural Language Processing (NLP) in Python
💫 Industrial-strength Natural Language Processing (NLP) in Python - explosion/spaCy