{"id":15940338,"url":"https://github.com/summitkwan/udacity_deeplearning","last_synced_at":"2025-04-03T20:41:58.919Z","repository":{"id":78602080,"uuid":"108089341","full_name":"SummitKwan/Udacity_DeepLearning","owner":"SummitKwan","description":null,"archived":false,"fork":false,"pushed_at":"2018-01-10T19:40:39.000Z","size":1668,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-09T08:44:29.203Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/SummitKwan.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,"publiccode":null,"codemeta":null}},"created_at":"2017-10-24T07:01:54.000Z","updated_at":"2017-10-24T07:04:27.000Z","dependencies_parsed_at":"2023-03-12T04:48:39.059Z","dependency_job_id":null,"html_url":"https://github.com/SummitKwan/Udacity_DeepLearning","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SummitKwan%2FUdacity_DeepLearning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SummitKwan%2FUdacity_DeepLearning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SummitKwan%2FUdacity_DeepLearning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SummitKwan%2FUdacity_DeepLearning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SummitKwan","download_url":"https://codeload.github.com/SummitKwan/Udacity_DeepLearning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247078783,"owners_count":20879950,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":"2024-10-07T06:41:16.797Z","updated_at":"2025-04-03T20:41:58.903Z","avatar_url":"https://github.com/SummitKwan.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"Assignments for Udacity Deep Learning class with TensorFlow\n===========================================================\n\nCourse information can be found at https://www.udacity.com/course/deep-learning--ud730\n\nRunning the Docker container from the Google Cloud repository\n-------------------------------------------------------------\n\n    docker run -p 8888:8888 --name tensorflow-udacity -it gcr.io/tensorflow/udacity-assignments:1.0.0\n\nNote that if you ever exit the container, you can return to it using:\n\n    docker start -ai tensorflow-udacity\n\nAccessing the Notebooks\n-----------------------\n\nOn linux, go to: http://127.0.0.1:8888\n\nOn mac, find the virtual machine's IP using:\n\n    docker-machine ip default\n\nThen go to: http://IP:8888 (likely http://192.168.99.100:8888)\n\nFAQ\n---\n\n* **I'm getting a MemoryError when loading data in the first notebook.**\n\nIf you're using a Mac, Docker works by running a VM locally (which\nis controlled by `docker-machine`). It's quite likely that you'll\nneed to bump up the amount of RAM allocated to the VM beyond the\ndefault (which is 1G).\n[This Stack Overflow question](http://stackoverflow.com/questions/32834082/how-to-increase-docker-machine-memory-mac)\nhas two good suggestions; we recommend using 8G.\n\nIn addition, you may need to pass `--memory=8g` as an extra argument to\n`docker run`.\n\n* **I want to create a new virtual machine instead of the default one.**\n\n`docker-machine` is a tool to provision and manage docker hosts, it supports multiple platform (ex. aws, gce, azure, virtualbox, ...). To create a new virtual machine locally with built-in docker engine, you can use\n\n    docker-machine create -d virtualbox --virtualbox-memory 8196 tensorflow\n    \n`-d` means the driver for the cloud platform, supported drivers listed [here](https://docs.docker.com/machine/drivers/). Here we use virtualbox to create a new virtual machine locally. `tensorflow` means the name of the virtual machine, feel free to use whatever you like. You can use\n\n    docker-machine ip tensorflow\n    \nto get the ip of the new virtual machine. To switch from default virtual machine to a new one (here we use tensorflow), type\n\n    eval $(docker-machine env tensorflow)\n    \nNote that `docker-machine env tensorflow` outputs some environment variables such like `DOCKER_HOST`. Then your docker client is now connected to the docker host in virtual machine `tensorflow`\n\n* **I'm getting a TLS connection error.**\n\nIf you get an error about the TLS connection of your docker, run the command below to confirm the problem.\n\n\tdocker-machine ip tensorflow\n\nThen if it is the case use the instructions on [this page](https://docs.docker.com/toolbox/faqs/troubleshoot/) to solve the issue.\n\n\n* **I'm getting the error - docker: Cannot connect to the Docker daemon. Is the docker daemon running on this host? - when I run 'docker run'.**\n\nThis is a permissions issue, and a popular answer is provided for Linux and Max OSX [here](http://stackoverflow.com/questions/21871479/docker-cant-connect-to-docker-daemon) on StackOverflow.\n\nNotes for anyone needing to build their own containers (mostly instructors)\n===========================================================================\n\nBuilding a local Docker container\n---------------------------------\n\n    cd tensorflow/examples/udacity\n    docker build --pull -t $USER/assignments .\n\nRunning the local container\n---------------------------\n\nTo run a disposable container:\n\n    docker run -p 8888:8888 -it --rm $USER/assignments\n\nNote the above command will create an ephemeral container and all data stored in the container will be lost when the container stops.\n\nTo avoid losing work between sessions in the container, it is recommended that you mount the `tensorflow/examples/udacity` directory into the container:\n\n    docker run -p 8888:8888 -v \u003c/path/to/tensorflow/examples/udacity\u003e:/notebooks -it --rm $USER/assignments\n\nThis will allow you to save work and have access to generated files on the host filesystem.\n\nPushing a Google Cloud release\n------------------------------\n\n    V=1.0.0\n    docker tag $USER/assignments gcr.io/tensorflow/udacity-assignments:$V\n    gcloud docker push gcr.io/tensorflow/udacity-assignments\n    docker tag $USER/assignments gcr.io/tensorflow/udacity-assignments:latest\n    gcloud docker push gcr.io/tensorflow/udacity-assignments\n\nHistory\n-------\n\n* 0.1.0: Initial release.\n* 0.2.0: Many fixes, including lower memory footprint and support for Python 3.\n* 0.3.0: Use 0.7.1 release.\n* 0.4.0: Move notMMNIST data for Google Cloud.\n* 0.5.0: Actually use 0.7.1 release.\n* 0.6.0: Update to TF 0.10.0, add libjpeg (for Pillow).\n* 1.0.0: Update to TF 1.0.0 release.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsummitkwan%2Fudacity_deeplearning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsummitkwan%2Fudacity_deeplearning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsummitkwan%2Fudacity_deeplearning/lists"}