Title: Commits · samueldinesh/pythonNNexample · GitHub
Open Graph Title: Commits · samueldinesh/pythonNNexample
X Title: Commits · samueldinesh/pythonNNexample
Description: Annotations for the Sirajology Python NN Example. This code comes from a demo NN program from the YouTube video https://youtu.be/h3l4qz76JhQ. The program creates an neural network that simulates the exclusive OR function with two inputs and one output. - Commits · samueldinesh/pythonNNexample
Open Graph Description: Annotations for the Sirajology Python NN Example. This code comes from a demo NN program from the YouTube video https://youtu.be/h3l4qz76JhQ. The program creates an neural network that simulates th...
X Description: Annotations for the Sirajology Python NN Example. This code comes from a demo NN program from the YouTube video https://youtu.be/h3l4qz76JhQ. The program creates an neural network that simulates th...
Opengraph URL: https://github.com/samueldinesh/pythonNNexample
X: @github
Domain: patch-diff.githubusercontent.com
| route-pattern | /:user_id/:repository/graphs/commit-activity(.:format) |
| route-controller | graphs |
| route-action | commit_activity |
| fetch-nonce | v2:db829e5e-3c88-6a56-3db5-fcd8f18138f9 |
| current-catalog-service-hash | b4d8436665c5448282b6f4eacc6394e6e8801de97cb226acdca9da20ae59be92 |
| request-id | C126:1AC151:17D5E59:2016CBE:698063EB |
| html-safe-nonce | e506018ae69d041d4d848bec5caac3339b1b01064484196cba2055994d563ebc |
| visitor-payload | eyJyZWZlcnJlciI6IiIsInJlcXVlc3RfaWQiOiJDMTI2OjFBQzE1MToxN0Q1RTU5OjIwMTZDQkU6Njk4MDYzRUIiLCJ2aXNpdG9yX2lkIjoiODcxNjI3MDA5NDcwOTE4NzU2MyIsInJlZ2lvbl9lZGdlIjoiaWFkIiwicmVnaW9uX3JlbmRlciI6ImlhZCJ9 |
| visitor-hmac | c57d38049714c19599b3d48655edf1dde6285e3aaf0154958cbf9125f94a476b |
| hovercard-subject-tag | repository:78125177 |
| github-keyboard-shortcuts | repository,copilot |
| google-site-verification | Apib7-x98H0j5cPqHWwSMm6dNU4GmODRoqxLiDzdx9I |
| octolytics-url | https://collector.github.com/github/collect |
| analytics-location | / |
| fb:app_id | 1401488693436528 |
| apple-itunes-app | app-id=1477376905, app-argument=https://github.com/samueldinesh/pythonNNexample/graphs/commit-activity |
| twitter:image | https://opengraph.githubassets.com/7c413629d775798689d44cee6065828efe066e526f91b6ac6d9f09c7aa270c69/samueldinesh/pythonNNexample |
| twitter:card | summary_large_image |
| og:image | https://opengraph.githubassets.com/7c413629d775798689d44cee6065828efe066e526f91b6ac6d9f09c7aa270c69/samueldinesh/pythonNNexample |
| og:image:alt | Annotations for the Sirajology Python NN Example. This code comes from a demo NN program from the YouTube video https://youtu.be/h3l4qz76JhQ. The program creates an neural network that simulates th... |
| og:image:width | 1200 |
| og:image:height | 600 |
| og:site_name | GitHub |
| og:type | object |
| hostname | github.com |
| expected-hostname | github.com |
| None | 60279d4097367e16897439d16d6bbe4180663db828c666eeed2656988ffe59f6 |
| turbo-cache-control | no-cache |
| go-import | github.com/samueldinesh/pythonNNexample git https://github.com/samueldinesh/pythonNNexample.git |
| octolytics-dimension-user_id | 13595885 |
| octolytics-dimension-user_login | samueldinesh |
| octolytics-dimension-repository_id | 78125177 |
| octolytics-dimension-repository_nwo | samueldinesh/pythonNNexample |
| octolytics-dimension-repository_public | true |
| octolytics-dimension-repository_is_fork | true |
| octolytics-dimension-repository_parent_id | 70839196 |
| octolytics-dimension-repository_parent_nwo | stmorgan/pythonNNexample |
| octolytics-dimension-repository_network_root_id | 70839196 |
| octolytics-dimension-repository_network_root_nwo | stmorgan/pythonNNexample |
| turbo-body-classes | logged-out env-production page-responsive |
| disable-turbo | false |
| browser-stats-url | https://api.github.com/_private/browser/stats |
| browser-errors-url | https://api.github.com/_private/browser/errors |
| release | c6a96cd078b54261c0aaa028bdbf4beca00718d1 |
| ui-target | full |
| theme-color | #1e2327 |
| color-scheme | light dark |
Links:
Viewport: width=device-width