{"id":40512002,"url":"https://github.com/sequenzia/photon","last_synced_at":"2026-01-20T20:12:38.885Z","repository":{"id":231458377,"uuid":"661433394","full_name":"sequenzia/photon","owner":"sequenzia","description":null,"archived":false,"fork":false,"pushed_at":"2024-04-04T03:48:16.000Z","size":236,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-29T01:08:02.395Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sequenzia.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2023-07-02T20:34:39.000Z","updated_at":"2024-04-03T01:55:52.000Z","dependencies_parsed_at":"2024-04-04T04:45:08.624Z","dependency_job_id":null,"html_url":"https://github.com/sequenzia/photon","commit_stats":null,"previous_names":["sequenzia/photon"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sequenzia/photon","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sequenzia%2Fphoton","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sequenzia%2Fphoton/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sequenzia%2Fphoton/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sequenzia%2Fphoton/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sequenzia","download_url":"https://codeload.github.com/sequenzia/photon/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sequenzia%2Fphoton/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28612166,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-20T18:56:40.769Z","status":"ssl_error","status_checked_at":"2026-01-20T18:54:26.653Z","response_time":117,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-01-20T20:12:38.821Z","updated_at":"2026-01-20T20:12:38.879Z","avatar_url":"https://github.com/sequenzia.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Photon: Machine Learning Framework\nA end-to-end Machine Learning ramework that extends the functionality of other frameworks such as TensorFlow \u0026 Keras. Photon ML is built to apply neural network and ensemble modeling techniques for deep learning financial algorithms. The framework supports the entire lifecycle of a machine learning project including data preparation, model development, training, monitoring, evaluation and deployment.\n\n**Key Features of Photon ML:**\n\n- Streamlines the development and implementation of end-to-end Machine Learning systems.\n- Custom object-oriented API with built-in subclassing of Keras and TensorFlow APIs.\n- Built-in custom modules such as Models, Layers, Optimizers and Loss Functions.\n- Highly customizable interface to extend built-in modules for specific algorithms/networks.\n- Detailed logging and analysis of model parameters to increase interpretability and optimization.\n- Works natively with TensorFlow distributed strategies.\n- Real-time data preprocessing; dataset splitting, normalization, scaling, aggregation \u0026 resampling.\n- Custom batching, padding and masking of data.\n- Designed to be model/algorithm agnostic and to work natively with container services.\n- Natively shares input \u0026 output between multiple networks to streamline deep ensemble learning.\n- Interface for saving, serializing and loading entire networks including learned \u0026 hyper parameters.\n- Custom dynamic learning rate scheduling.\n\n---\n**Photon ML Examples:** https://github.com/sequenzia/photon_examples\n\n**A Collection of Algorthims/Models designed with Photon ML:** https://github.com/sequenzia/dyson\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsequenzia%2Fphoton","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsequenzia%2Fphoton","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsequenzia%2Fphoton/lists"}