{"id":15159344,"url":"https://github.com/prakhr/coursera-specializations","last_synced_at":"2026-03-01T18:03:02.393Z","repository":{"id":61921961,"uuid":"236348226","full_name":"prakHr/Coursera-Specializations","owner":"prakHr","description":"Contains courses in specializations of coursera on deep learning","archived":false,"fork":false,"pushed_at":"2023-05-20T13:14:21.000Z","size":16956,"stargazers_count":1,"open_issues_count":0,"forks_count":3,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-16T16:51:45.050Z","etag":null,"topics":["cats-vs-dogs","convolutional-neural-networks","embedding-layer-keras","fashion-mnist-dataset","iris-classification","keras-implementations","mnist","mnist-handwriting-recognition","mobilenet","python3","rock-paper-scissors","tensorflow-models","tensorflowjs","toxicity","transfer-learning","wdbc"],"latest_commit_sha":null,"homepage":"https://www.deeplearning.ai/deep-learning-specialization/","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/prakHr.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":"2020-01-26T17:27:32.000Z","updated_at":"2022-12-14T23:11:24.000Z","dependencies_parsed_at":"2024-09-02T16:30:36.101Z","dependency_job_id":"da8a2d28-f6f5-4b30-a1c9-73b49e31ab51","html_url":"https://github.com/prakHr/Coursera-Specializations","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/prakHr%2FCoursera-Specializations","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prakHr%2FCoursera-Specializations/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prakHr%2FCoursera-Specializations/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prakHr%2FCoursera-Specializations/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/prakHr","download_url":"https://codeload.github.com/prakHr/Coursera-Specializations/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246781994,"owners_count":20832950,"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":["cats-vs-dogs","convolutional-neural-networks","embedding-layer-keras","fashion-mnist-dataset","iris-classification","keras-implementations","mnist","mnist-handwriting-recognition","mobilenet","python3","rock-paper-scissors","tensorflow-models","tensorflowjs","toxicity","transfer-learning","wdbc"],"created_at":"2024-09-26T21:05:02.629Z","updated_at":"2026-03-01T18:03:02.348Z","avatar_url":"https://github.com/prakHr.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Coursera-Specializations on CNNs\n[Coursera Specializations] - Python-Javascript-Programming-Tensorflow-Algorithms-Deployment \nSimple predictions and algorithms implemented with tensorflow and google colab(courses has the colab environment setup)  \nYou can download 200 OK! from __[web apps](https://chrome.google.com/webstore/detail/web-server-for-chrome/ofhbbkphhbklhfoeikjpcbhemlocgigb?hl=en)__ and other project material from __[here](https://github.com/lmoroney/dlaicourse \"Specializations\")__\n\n\n\u003cimg src=\"https://s3.amazonaws.com/coursera/media/Partner_Logos.png\" width=\"480\" height=\"300\"\u003e\n\n## Table of contents\n* [Learnt Skills](#learnt)\n* [Setup](#setup)\n* [Modules](#modules)\n* [Certificate](#certificates)\n\n---\n### Learnt\nYou will learn how to use different methods of tensorflow, in other words to build a pipeline from __preprocessing steps__ to building models and finally __saving models in a necessary format__. You will also use javascript modules to __read from csv files__ and predict outputs. \n\nThen you will learn what are __the necessary layers to put__ in different courses while building CNNs from scratch.\n\nApart from that you will learn hypertuning a parameter, how tweaking them affects your accuracy and convergence as well as instability.\n\n---\n\n### Setup\nThe __Sublime Text__ for writing javascript Environment download, documentation, and programming resources are available at: https://www.sublimetext.com/3. \n\nI prefer setting up a anaconda environment, this way you can install different versions of tensorflow easily. \n\nOr learn by running scripts on google colab using their sweet gpu for increased runtime(Note that your variables and files will get lost after a fresh run in colab).\n\n---\n\n### Modules\n* tensorflow\n* keras\n* shutil\n* zipfile\n* random\n* google.colab\n* numpy\n* json\n* matplotlib\n\n---\n\n\n### Certificates\nyou can get a certificate like [this](https://www.coursera.org/account/accomplishments/specialization/certificate/PKMVM99Q5MSE \"Certified by coursera people\") if not choose to audit the course\n\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprakhr%2Fcoursera-specializations","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprakhr%2Fcoursera-specializations","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprakhr%2Fcoursera-specializations/lists"}