{"id":22419092,"url":"https://github.com/en10/ai-intro","last_synced_at":"2026-05-01T15:39:39.109Z","repository":{"id":75872064,"uuid":"183767513","full_name":"EN10/AI-Intro","owner":"EN10","description":"Intro to Tensorflow, Keras and MNIST","archived":false,"fork":false,"pushed_at":"2019-04-28T10:06:57.000Z","size":7,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-27T04:32:09.652Z","etag":null,"topics":["keras","mnist","tensorflow"],"latest_commit_sha":null,"homepage":"","language":null,"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/EN10.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":"2019-04-27T12:02:58.000Z","updated_at":"2019-04-28T10:06:59.000Z","dependencies_parsed_at":"2023-02-24T10:15:23.401Z","dependency_job_id":null,"html_url":"https://github.com/EN10/AI-Intro","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/EN10/AI-Intro","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EN10%2FAI-Intro","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EN10%2FAI-Intro/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EN10%2FAI-Intro/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EN10%2FAI-Intro/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EN10","download_url":"https://codeload.github.com/EN10/AI-Intro/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EN10%2FAI-Intro/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32503203,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-30T13:12:12.517Z","status":"online","status_checked_at":"2026-05-01T02:00:05.856Z","response_time":64,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["keras","mnist","tensorflow"],"created_at":"2024-12-05T16:14:08.603Z","updated_at":"2026-05-01T15:39:39.095Z","avatar_url":"https://github.com/EN10.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# AI Intro\n\nSome of the key Libraries and Dataset used:     \n* [Colab](https://colab.research.google.com/notebooks/welcome.ipynb) a free progarmming environment. \n* [Tensorflow](https://en.wikipedia.org/wiki/TensorFlow) as an AI Library created by Google and can be used in Python.    \n* [Keras](https://en.wikipedia.org/wiki/Keras) Also a Python AI library, it is used on top of Tensorflow. It allows models to be created faster and more easily than with Tensorflow alone.   \n* [MNIST](https://en.wikipedia.org/wiki/MNIST_database) A collection of 70,000 handwritten digits from 0-9, it is a commonly used dataset for training neural networks.   \n![alt text](https://upload.wikimedia.org/wikipedia/commons/2/27/MnistExamples.png \"MNIST\")    \n\n## Code Example\n```python\n# Point to the MNIST tensorflow directory\nfrom tensorflow.examples.tutorials.mnist import input_data\n# Downloads and formats MNIST\nmnist = input_data.read_data_sets(\"./mnist\", one_hot=True)\n\nimport keras\nmodel = keras.models.Sequential()\n# See model Image below, 784 pixels on the left and 10 neurons on the right\nmodel.add(keras.layers.Dense(10, activation='softmax', input_shape=(784,)))\n\nmodel.compile(optimizer='adam', \n              loss='categorical_crossentropy',\n              metrics=['accuracy'])\n\n# Trains the model by feeding 60,000 images\nmodel.fit(mnist.train.images, mnist.train.labels,\n          epochs=5)\n\n# Tests the model with 10,000 new test images\nmodel.evaluate(mnist.test.images, mnist.test.labels)\n```\nModel: ![alt text](https://ml4a.github.io/images/figures/mnist_1layer.png \"Model\")  \n[Softmax](https://en.wikipedia.org/wiki/Softmax_function)   \n[Adam](https://en.wikipedia.org/wiki/Stochastic_gradient_descent#Adam)  \n\n## References\n\n* [EN10 Keras MNIST](https://github.com/EN10/KerasMNIST)\n* [Keras Docs](https://keras.io/getting-started/sequential-model-guide)\n* [Tensorflow Fashion MNIST](https://www.tensorflow.org/tutorials/keras/basic_classification)\n* [Udacity TF Intro](https://eu.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fen10%2Fai-intro","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fen10%2Fai-intro","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fen10%2Fai-intro/lists"}