{"id":28744901,"url":"https://github.com/mvanzulli/mlspecialization_deeplearningia","last_synced_at":"2026-04-28T17:04:57.768Z","repository":{"id":112506248,"uuid":"521054744","full_name":"mvanzulli/MLSpecialization_DeepLearningIA","owner":"mvanzulli","description":"This repo contains the files implemented thorough the Machine Learning Specialization offered by DeepLearning.IA ","archived":false,"fork":false,"pushed_at":"2022-12-17T17:50:13.000Z","size":5553,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-16T12:08:24.944Z","etag":null,"topics":["coursera","deeplearning-ai","machine-learning","python","supervised-learning","tensorflow","unsupervised-learning"],"latest_commit_sha":null,"homepage":"","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/mvanzulli.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,"zenodo":null}},"created_at":"2022-08-03T22:51:28.000Z","updated_at":"2023-03-29T14:19:04.000Z","dependencies_parsed_at":"2023-05-15T12:30:08.856Z","dependency_job_id":null,"html_url":"https://github.com/mvanzulli/MLSpecialization_DeepLearningIA","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mvanzulli/MLSpecialization_DeepLearningIA","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mvanzulli%2FMLSpecialization_DeepLearningIA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mvanzulli%2FMLSpecialization_DeepLearningIA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mvanzulli%2FMLSpecialization_DeepLearningIA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mvanzulli%2FMLSpecialization_DeepLearningIA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mvanzulli","download_url":"https://codeload.github.com/mvanzulli/MLSpecialization_DeepLearningIA/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mvanzulli%2FMLSpecialization_DeepLearningIA/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32390122,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-28T14:34:11.604Z","status":"ssl_error","status_checked_at":"2026-04-28T14:32:37.009Z","response_time":56,"last_error":"SSL_read: 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":["coursera","deeplearning-ai","machine-learning","python","supervised-learning","tensorflow","unsupervised-learning"],"created_at":"2025-06-16T12:08:21.307Z","updated_at":"2026-04-28T17:04:57.759Z","avatar_url":"https://github.com/mvanzulli.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MLSpecialization_DeepLearningIA\n\nContains Solutions and Notes for the [Machine Learning Specialization](https://www.coursera.org/specializations/machine-learning-introduction/?utm_medium=coursera\u0026utm_source=home-page\u0026utm_campaign=mlslaunch2022IN) by Andrew NG on Coursera \n\n## Course 1 : [Supervised Machine Learning: Regression and Classification](https://www.coursera.org/learn/machine-learning?specialization=machine-learning-introduction)\n\n- [Week 1]()\n\n    - Regression\n    - Supervised vs unsupervised learning\n    - Model Representation\n    - Cost Function\n    - Gradient Descent\n\n\u003cbr/\u003e\n\n- [Week 2]() \n\n    - Gradient descent.\n    - Multiple linear regression\n    - Numpy Vectorization\n    - Multi Variate Regression\n    - Feature Scaling\n    - Feature Engineering\n    - Linear Regression\n\n\u003cbr/\u003e\n\n- [Week 3](/C1%20-%20Supervised%20Machine%20Learning%3A%20Regression%20and%20Classification/week3/)\n\n    - Cost function and gradient descent for logistic regression\n    - Classification\n    - Sigmoid Function\n    - Decision Boundary\n    - Logistic Loss\n    - Overfitting\n    - Regularization\n    - Logistic Regression\n\n#### [Certificate Of Completion](https://www.coursera.org/account/accomplishments/certificate/6JRLLW8JRM3A)\n\n\u003cbr/\u003e\n\n## Course 2 : [Advanced Learning Algorithms](https://www.coursera.org/learn/advanced-learning-algorithms?specialization=machine-learning-introduction)\n\n- [Week 1]()\n    - Neural networks model and intuition\n    - TensorFlow implementation\n    - Neural Networks Implementation in Numpy\n    - Neurons and Layers\n    - Neural Networks for Binary Classification\n\u003cbr/\u003e\n\n\n- [Week 2]()\n    - Neural Networks Training\n    - Activation Functions\n    - Multiclass Classification\n    - RElu\n    - Softmax\n    - Neural Networks For Handwritten Digit Recognition \n\n\u003cbr/\u003e\n\n- [Week 3]()\n    - Bias and Variance\n    - Machine Learning Development Process\n\n\u003cbr/\u003e\n\n\n- [Week 4]()\n    - Decision Trees\n    - Decision Trees Learning\n    - Decision Trees Ensembles\n\n#### [Certificate of Completion](https://www.coursera.org/account/accomplishments/certificate/US3R9FWCGTFW)        \n\n\u003cbr/\u003e\n\n## Course 3 : [Unsupervised Learning, Recommenders, Reinforcement Learning](https://www.coursera.org/learn/unsupervised-learning-recommenders-reinforcement-learning?specialization=machine-learning-introduction)\n\n\u003cbr/\u003e\n\n- [Week 1]()\n    - Clustering\n    - Anomaly Detection\n    - K means\n    - Anomaly Detection\n\u003cbr/\u003e\n\n- [Week 2]()\n    - Collaborative Filtering\n    - Recommender systems implementation\n    - Content-based filtering\n    - Collaborative Filtering RecSys\n    - RecSys using Neural Networks\n\u003cbr/\u003e\n\n- [Week 3]()\n    - Reinforcement learning\n    - State-action value function\n    - Continuous state spaces\n    - Deep Q-Learning - Lunar Lander Example\n\n\n#### [Certificate of Completion](https://www.coursera.org/account/accomplishments/certificate/6JRLLW8JRM3A)\n\n\n### [Specialization Certificate](https://coursera.org/share/9d21590225c4716a984bd4eeb8592d85)\n\n\n### Course Review :\n\nThis Course is a great place to start and get into Machine Learning algorithms. \n\n**Special thanks to [Professor Andrew Ng](https://www.andrewng.org/) for structuring and tailoring this Course.**\n\n\u003cbr/\u003e\n\n\u003chr/\u003e\n\n#### Some results :\n\n* \u003ci\u003eWrite an unsupervised learning algorithm to **Land the Lunar Lander** Using Deep Q-Learning\u003c/i\u003e\n\n    - The Rover was trained to land correctly on the surface, correctly between the flags as indicators after many unsuccessful attempts in learning how to do it.\n    - The final landing after training the agent using appropriate parameters : \n\nhttps://user-images.githubusercontent.com/77543865/182395635-703ae199-ba79-4940-86eb-23dd90093ab3.mp4\n\n* \u003ci\u003eWrite an algorithm for a **Movie Recommender System**\u003c/i\u003e\n    \n    - A movie database is collected based on its genre.\n    - A content based filtering and collaborative filtering algorithm is trained and the movie recommender system is implemented.\n    - It gives movie recommendentations based on the movie genre.\n\n![movie_recommendation](https://user-images.githubusercontent.com/77543865/182398093-c7387754-34a9-4044-b842-0085060c3525.png)\n\n\n## Bugs and feature requests\n\nHave a bug or a feature request? Please first read the [issue guidelines](https://reponame/blob/master/CONTRIBUTING.md) and search for existing and closed issues. If your problem or idea is not addressed yet, [please open a new issue](https://reponame/issues/new).\n\n\n\n## Creators\n\n- \u003chttps://github.com/mvanzulli\u003e\n\n\n\n\n\n## Copyright and license\n\nCode and documentation copyright 2022 the authors. Code released under the [MIT License](https://reponame/blob/master/LICENSE).\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmvanzulli%2Fmlspecialization_deeplearningia","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmvanzulli%2Fmlspecialization_deeplearningia","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmvanzulli%2Fmlspecialization_deeplearningia/lists"}