{"id":20562766,"url":"https://github.com/mint-lab/dl_tutorial","last_synced_at":"2025-10-28T07:37:13.773Z","repository":{"id":145858887,"uuid":"359353806","full_name":"mint-lab/dl_tutorial","owner":"mint-lab","description":"Machine Learning and Deep Learning Tutorial","archived":false,"fork":false,"pushed_at":"2024-12-05T07:45:20.000Z","size":20234,"stargazers_count":16,"open_issues_count":0,"forks_count":5,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-09T13:11:43.517Z","etag":null,"topics":["deep-learning","dl","machine-learning","ml","pytorch","sckit-learn"],"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/mint-lab.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":"2021-04-19T06:34:37.000Z","updated_at":"2025-06-16T16:54:07.000Z","dependencies_parsed_at":null,"dependency_job_id":"115b1225-f058-47d4-a776-acbf06edd6d1","html_url":"https://github.com/mint-lab/dl_tutorial","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/mint-lab/dl_tutorial","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mint-lab%2Fdl_tutorial","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mint-lab%2Fdl_tutorial/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mint-lab%2Fdl_tutorial/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mint-lab%2Fdl_tutorial/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mint-lab","download_url":"https://codeload.github.com/mint-lab/dl_tutorial/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mint-lab%2Fdl_tutorial/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":281403400,"owners_count":26495042,"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","status":"online","status_checked_at":"2025-10-28T02:00:06.022Z","response_time":60,"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":["deep-learning","dl","machine-learning","ml","pytorch","sckit-learn"],"created_at":"2024-11-16T04:13:25.808Z","updated_at":"2025-10-28T07:37:13.757Z","avatar_url":"https://github.com/mint-lab.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"## Machine Learning and Deep Learning Tutorial\n_Machine Learning and Deep learning Tutorial_ (shortly _ML/DL Tutorial_) has been initiated to teach undergraduate students in [SEOULTECH](https://en.seoultech.ac.kr/) about basic concepts of machine learning and deep learning with hands-on practices using [scikit-learn](https://scikit-learn.org/) and  [PyTorch](https://pytorch.org/). Even though there are so many good lectures and tutorials on machine learning and deep learning, I would like to share my viewpoint and summary with humble slides and examples because I also have learned many things from open and public lectures, tutorials, and articles. I hope that my slides and examples are also helpful to others.\n\n* To clone this repository (codes and slides): `git clone https://github.com/mint-lab/dl_tutorial.git`\n* To fork this repository to your Github: [Click here](https://github.com/mint-lab/dl_tutorial/fork)\n* To download codes and slides as a ZIP file: [Click here](https://github.com/mint-lab/dl_tutorial/archive/master.zip)\n\nThis tutorial is the last part of my lecture. Its prior knowledge on Python and mathematics is also available in _[Programming Meets Mathematics](https://github.com/mint-lab/prog_meets_math)_.\n\n\n\n### ML/DL Lecture Slides\n* [Machine Learning with scikit-learn](https://github.com/mint-lab/dl_tutorial/blob/master/slides/ml_tutorial.pdf)\n* [Deep Learning with PyTorch](https://github.com/mint-lab/dl_tutorial/blob/master/slides/dl_tutorial.pdf)\n\n\n\n### ML Example Codes\n:memo: Source codes are enumerated in the order of [its lecture slides](https://github.com/mint-lab/dl_tutorial/blob/master/slides/ml_tutorial.pdf).\n* **scikit-learn**\n  * [Three Steps of scikit-learn: Instantiation, `fit` and `predict`](https://github.com/mint-lab/dl_tutorial/blob/master/examples/iris_classification.py)\n* **Classification**\n  * [SVM Classifiers](https://github.com/mint-lab/dl_tutorial/blob/master/examples/iris_classification_svm.py)\n  * [Decision Tree Classifiers](https://github.com/mint-lab/dl_tutorial/blob/master/examples/iris_classification_tree.py)\n  * [Naive Bayes Classifiers](https://github.com/mint-lab/dl_tutorial/blob/master/examples/iris_classification_bayes.py)\n  * [More Classifiers](https://github.com/mint-lab/dl_tutorial/blob/master/examples/iris_classification_more.py)\n  * Lab) Breast Cancer Classification [[slides]](https://github.com/mint-lab/dl_tutorial/blob/master/slides/ml01_lab.pdf) [[skeleton code]](https://github.com/mint-lab/dl_tutorial/blob/master/examples/wdbc_classification_skeleton.py)\n* **Regression**\n  * [Linear Regression](https://github.com/mint-lab/dl_tutorial/blob/master/examples/line_fitting_sklearn.py)\n* **Clustering**\n  * [K-means Clustering](https://github.com/mint-lab/dl_tutorial/blob/master/examples/iris_clustering_kmeans.py)\n* **Data Separation**\n  * Lab) Breast Cancer Classification with Cross-validation [[slides]](https://github.com/mint-lab/dl_tutorial/blob/master/slides/ml02_lab.pdf) [[skeleton code]](https://github.com/mint-lab/dl_tutorial/blob/master/examples/wdbc_classification_cv.py)\n\n\n\n\n### DL Example Codes\n:memo: Source codes are enumerated in the order of [its lecture slides](https://github.com/mint-lab/dl_tutorial/blob/master/slides/dl_tutorial.pdf).\n\n* **PyTorch**\n  * [Creating a Tensor](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch01_create_tensor.py)\n  * [Reshaping a Tensor](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch02_reshape_tensor.py)\n  * [Line Fitting from Two Points](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch03_line_fitting.py)\n  * [CPU vs. GPU-acceleration](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch04_cpu_vs_gpu.py)\n  * [Automatic Differentiation](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch05_autograd.py)\n  * [Automatic Differentiation - More Analysis](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch05_autograd_analysis.py)\n  * [Gradient Descent by Hands](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch06_grad_descent.py)\n  * [Gradient Descent by `torch.optim`](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch06_grad_descent_optimizer.py)\n  * Lab) Object Detection using YOLO [[slides]](https://github.com/mint-lab/dl_tutorial/blob/master/slides/dl01_lab.pdf) [[skeleton code (py)]](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch_yolo.py) [[skeleton code (ipynb)]](https://github.com/mint-lab/dl_tutorial/blob/master/examples/pytorch_yolo.ipynb)\n* **Neural Network**\n  * [Visualizing Activation Functions](https://github.com/mint-lab/dl_tutorial/blob/master/examples/dnn_basic_activation_func.py)\n  * [Observing Vanishing Gradient - Sigmoid](https://github.com/mint-lab/dl_tutorial/blob/master/examples/dnn_basic_vanishing_grad.py)\n  * [Observing Vanishing Gradient - ReLU](https://github.com/mint-lab/dl_tutorial/blob/master/examples/dnn_basic_vanishing_grad_relu.py)\n  * The Iris Flower Dataset [[UCI ML Repository]](https://archive.ics.uci.edu/ml/datasets/iris)\n    * [Iris Flower Classification - No Class](https://github.com/mint-lab/dl_tutorial/blob/master/examples/dnn_iris2_no_class.py)\n    * [Iris Flower Classification - My Style](https://github.com/mint-lab/dl_tutorial/blob/master/examples/dnn_iris2.py)\n* **Convolutional Neural Network**\n  * The MNIST Dataset [[homepage]](http://yann.lecun.com/exdb/mnist/)\n    * [Loading the MNIST Dataset](https://github.com/mint-lab/dl_tutorial/blob/master/examples/cnn_mnist_dataset.py)\n    * [Digit Classificaiton with the MNIST Dataset](https://github.com/mint-lab/dl_tutorial/blob/master/examples/cnn_mnist.py)\n    * [Loading My Network and Testing It](https://github.com/mint-lab/dl_tutorial/blob/master/examples/cnn_mnist_load.py)\n    * [Different Styles for NN Classes](https://github.com/mint-lab/dl_tutorial/blob/master/examples/cnn_mnist_class_style.py)\n  * [Visualizing Learning Rate Schedulers](https://github.com/mint-lab/dl_tutorial/blob/master/examples/cnn_basic_lr_scheduler.py)\n* **Recurrent Neural Network**\n  * The Name2Lang Dataset [[homepage]](https://pytorch.org/tutorials/intermediate/char_rnn_classification_tutorial)\n    * [Name2Lang Classification with a Character-level RNN](https://github.com/mint-lab/dl_tutorial/blob/master/examples/rnn_name2lang.py)\n\n\u003e **Note)** All examples contain their basic NN architectures and hyperparameters. One of main objectives in practices will be their performance improvement by changing the architectures and selecting hyperparameters.\n\n\n\n### License\n* [Beerware](http://en.wikipedia.org/wiki/Beerware)\n\n\n\n### Authors\n* [Sunglok Choi](http://mint-lab.github.io/sunglok)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmint-lab%2Fdl_tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmint-lab%2Fdl_tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmint-lab%2Fdl_tutorial/lists"}