Deep Learning with R

Deep Learning with R https://bios691-deep-learning-r-2025.netlify.app/class/ Deep Learning with R Source Themes Academic (https://sourcethemes.com/academic/)enMGD https://bios691-deep-learning-r-2025.netlify.app/img/social-image.png Deep Learning with R https://bios691-deep-learning-r-2025.netlify.app/class/ Section 9: Best practices and summary https://bios691-deep-learning-r-2025.netlify.app/class/09-class/ Wed, 30 Apr 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/09-class/ <div id="best-practices" class="section level3"> <h3>Best practices</h3> <p><a href="../../slides/ch13_Best_Practices.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch13_Best_Practices.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="summary" class="section level3"> <h3>Summary</h3> <p><a href="../../slides/ch13_Overview.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch13_Overview.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="references" class="section level3"> <h3>References</h3> <ul> <li><a href="https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI">MIT 6.S191: Introduction to Deep Learning</a></li> <li><a href="https://www.youtube.com/@3blue1brown/playlists">3Blue1Brown</a></li> <li><a href="https://github.com/mdozmorov/MachineLearning_notes">MachineLearning_notes</a></li> </ul> </div> Section 8: Generative Deep Learning https://bios691-deep-learning-r-2025.netlify.app/class/08-class/ Wed, 23 Apr 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/08-class/ <div id="generative-deep-learningcd" class="section level3"> <h3>Generative Deep Learningcd</h3> <p><a href="../../slides/ch12_GAN01_Text_generation.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch12_GAN01_Text_generation.html#1" width="672" height="400px" data-external="1"> </iframe> <p><a href="../../slides/ch12_GAN02_Image_generation.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch12_GAN02_Image_generation.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="code" class="section level3"> <h3>Code</h3> <ul> <li>Text generation, <a href="../../slides/code/ch12_GAN01_Text_generation_code.Rmd">RMarkdown</a></li> <li>DeepDream, <a href="../../slides/code/ch12_GAN02_DeepDream_code.Rmd">RMarkdown</a></li> <li>Style transfer, <a href="../../slides/code/ch12_GAN03_Style_transfer_code.Rmd">RMarkdown</a></li> <li>Autoencoder, <a href="../../slides/code/ch12_GAN04_Autoencoder_code.Rmd">RMarkdown</a></li> <li>Generative Adversarial Network, <a href="../../slides/code/ch12_GAN05_Generative_adversarial_network_code.Rmd">RMarkdown</a></li> </ul> </div> Section 7: Deep Learning for Text https://bios691-deep-learning-r-2025.netlify.app/class/07-class/ Tue, 25 Mar 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/07-class/ <div id="deep-learning-for-text" class="section level3"> <h3>Deep Learning for Text</h3> <p><a href="../../slides/ch11a_Text_encoding.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch11a_Text_encoding.html#1" width="672" height="400px" data-external="1"> </iframe> <p><a href="../../slides/ch11b_Text_transformers.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch11b_Text_transformers.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="code" class="section level3"> <h3>Code</h3> <ul> <li>Text vectorization, embedding, <a href="../../slides/code/ch11_Text_encoding_code.Rmd">RMarkdown</a></li> <li>Reusing Word2vec embeddings, <a href="../../slides/code/ch11_Text_word2vec_code.Rmd">RMarkdown</a></li> <li>Attention math demo, <a href="../../slides/code/ch11_Text_attention_code.Rmd">RMarkdown</a></li> <li>Transformed architecture, <a href="../../slides/code/ch11_Text_transformers_code.Rmd">RMarkdown</a>  </li> </ul>       </div> <div id="references" class="section level3"> <h3>References</h3> <ul> <li><a href="https://text2vec.org/vectorization.html">Text analysis pipeline</a> - text2vec tutorials</li> <li><a href="https://towardsdatascience.com/nlp-illustrated-part-3-word2vec-5b2e12b6a63b/">NLP Illustrated, Part 3: Word2Vec</a> - word2vec illustrated guide</li> <li>Vaswani, Ashish, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. “Attention is all you need.” Advances in neural information processing systems 30 (2017). <a href="https://arxiv.org/abs/1706.03762" class="uri">https://arxiv.org/abs/1706.03762</a></li> <li><a href="https://github.com/rasbt/LLMs-from-scratch">LLMs-from-scratch</a> - Implement a ChatGPT-like LLM in PyTorch from scratch, step by step. <a href="https://youtube.com/playlist?list=PLTKMiZHVd_2IIEsoJrWACkIxLRdfMlw11">Youtube playlist</a></li> </ul>  </div> Section 6: Deep Learning for Time Series https://bios691-deep-learning-r-2025.netlify.app/class/06-class/ Mon, 17 Mar 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/06-class/ <div id="deep-learning-for-time-series" class="section level3"> <h3>Deep Learning for Time Series</h3> <p><a href="../../slides/ch10_RNN_slides.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch10_RNN_slides.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="code" class="section level3"> <h3>Code</h3> <ul> <li>Introduction to deep learning for sequence (time series) analysis, <a href="../../slides/code/ch10_RNN_code.Rmd">RMarkdown</a></li> </ul> </div> <div id="datasets" class="section level3"> <h3>Datasets</h3>  <ul> <li><a href="https://www.kaggle.com/datasets/whenamancodes/netflix-stock-market-analysis-founding-years">Netflix | Stock Market Analysis | Founding Years</a></li> </ul>     </div> <div id="references" class="section level3"> <h3>References</h3> <ul> <li><a href="https://colah.github.io/posts/2015-08-Understanding-LSTMs/">Understanding LSTM Networks</a></li> </ul> </div> Section 5: Convolutional Neural Network https://bios691-deep-learning-r-2025.netlify.app/class/05-class/ Mon, 10 Feb 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/05-class/ <div id="convolutional-neural-networks" class="section level3"> <h3>Convolutional Neural Networks</h3> <p><a href="../../slides/ch08_CNN_slides.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch08_CNN_slides.html#1" width="672" height="400px" data-external="1"> </iframe> <p><a href="../../slides/ch09_CNN_slides.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch09_CNN_slides.html#1" width="672" height="400px" data-external="1"> </iframe> <p><a href="../../slides/ch08_Glossary_slides.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch08_Glossary_slides.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="code" class="section level3"> <h3>Code</h3> <ul> <li><p>Introduction to deep learning for computer vision, <a href="../../slides/code/ch08_CNN_code1.Rmd">RMarkdown, part 1</a>, <a href="../../slides/code/ch08_CNN_code2.Rmd">RMarkdown, part 2</a></p></li> <li><p>Image segmentation example, <a href="../../slides/code/ch09_CNN_code1.Rmd">RMarkdown</a></p></li> <li><p>Modern convnet architecture patterns, <a href="../../slides/code/ch09_CNN_code2.Rmd">RMarkdown</a></p></li> <li><p>Interpreting what convnets learn, <a href="../../slides/code/ch09_CNN_code1.Rmd">RMarkdown</a></p></li> </ul> </div> <div id="references" class="section level3"> <h3>References</h3> <ul> <li><p>Computer vision & CNNs: MNIST revisted. by Brad Boehmke. <a href="https://rstudio-conf-2020.github.io/dl-keras-tf/04-computer-vision-cnns.html#1">Slides</a></p></li> <li><p>“How Convolutional Neural Networks work” - 26min video by Brandon Rohrer, <a href="https://youtu.be/FmpDIaiMIeA?feature=shared" class="uri">https://youtu.be/FmpDIaiMIeA?feature=shared</a></p></li> <li><p><a href="https://cs231n.github.io/convolutional-networks/">Convolutional Neural Networks (CNNs / ConvNets)</a> - notes from the Stanford CS class CS231n: Convolutional Neural Networks for Visual Recognition. <a href="https://cs231n.github.io/" class="uri">https://cs231n.github.io/</a></p></li> <li><p><a href="https://leonardoaraujosantos.gitbook.io/artificial-inteligence/machine_learning/deep_learning/convolution">Convolution</a> - detailed review of each operation and layer of a CNN</p></li> </ul> </div> Section 4: Deep dive into Keras https://bios691-deep-learning-r-2025.netlify.app/class/04-class/ Mon, 03 Feb 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/04-class/ <div id="in-class-exercises" class="section level1"> <h1>In-class exercises</h1> <p>Classifying movie reviews, sentiment analysis: a binary classification example, <a href="../../slides/code/04_Classifying_movie_review_code.Rmd">RMarkdown</a></p> <p>Classifying newswires: a multi-class classification example, with questions, <a href="../../slides/code/04_Classifying_newswires_code.Rmd">RMarkdown</a></p> </div> <div id="working-with-keras-a-deep-dive" class="section level1"> <h1>Working with Keras: A Deep Dive</h1> <p><a href="../../slides/ch06_DL_Workflow_slides.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch06_DL_Workflow_slides.html#1" width="672" height="400px" data-external="1"> </iframe> <p><a href="../../slides/ch07_Keras_deep_dive_slides.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/ch07_Keras_deep_dive_slides.html#1" width="672" height="400px" data-external="1"> </iframe> <p>Different ways to build Keras models, <a href="../../slides/code/ch07_2_Keras_models_code.Rmd">RMarkdown</a></p> <p>Training and evaluation loops and metrics, <a href="../../slides/code/ch07_3_loops_metrics_code.Rmd">RMarkdown</a></p> <p>Writing your own training and evaluation loops, <a href="../../slides/code/ch07_4_custom_training_evaluation_code.Rmd">RMarkdown</a></p> </div> Section 3: Data representations for neural network, Keras, Tensorflow https://bios691-deep-learning-r-2025.netlify.app/class/03-class/ Mon, 27 Jan 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/03-class/ <div id="slides" class="section level2"> <h2>Slides</h2> <div id="foundations-of-deep-learning-mathematical-definitions-data-representation" class="section level3"> <h3>Foundations of Deep learning, Mathematical definitions, Data representation</h3> <p><a href="../../slides/02b_data_tensorflow_gradient.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/02b_data_tensorflow_gradient.html#1" width="672" height="400px" data-external="1"> </iframe> <p><a href="../../slides/02b_data_tensorflow_gradient.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/03a_keras_tensorflow.html#1" width="672" height="400px" data-external="1"> </iframe> <p><a href="../../slides/03b_Model_optimization.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/03b_Model_optimization.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="introduction-to-keras-and-tensorflow" class="section level3"> <h3>Introduction to Keras and Tensorflow</h3> <p>Tensor data types, Keras API, <a href="../../slides/code/ch03_Tensorflow_Introduction_code.Rmd">RMarkdown</a></p> </div> </div> Section 2: Fundamentals of Deep Learning II https://bios691-deep-learning-r-2025.netlify.app/class/02-class/ Wed, 22 Jan 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/02-class/ <div id="slides" class="section level2"> <h2>Slides</h2> <div id="mathematical-foundations" class="section level3"> <h3>Mathematical Foundations</h3> <p><a href="../../slides/02a_first_neural_network.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/02a_first_neural_network.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="hello-deep-learning-world" class="section level3"> <h3>Hello [Deep Learning] World</h3> <p>MNIST classification example, <a href="../../slides/code/ch02_MNIST_code.Rmd">RMarkdown</a></p> </div> </div> Section 1: Fundamentals of Deep Learning I https://bios691-deep-learning-r-2025.netlify.app/class/01-class/ Mon, 13 Jan 2025 00:00:00 +0000 https://bios691-deep-learning-r-2025.netlify.app/class/01-class/ <div id="slides" class="section level2"> <h2>Slides</h2> <div id="ai-machine-learning-deep-learning-concepts" class="section level3"> <h3>AI, Machine Learning, Deep Learning concepts</h3> <p><a href="../../slides/01a_What_is_DL.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/01a_What_is_DL.html#1" width="672" height="400px" data-external="1"> </iframe> </div> <div id="brief-history-of-machine-learning" class="section level3"> <h3>Brief History of Machine Learning</h3> <p><a href="../../slides/01b_History.html#1" target="_blank">Lecture slides in HTML format</a></p> <iframe src="../../slides/01b_History.html#1" width="672" height="400px" data-external="1"> </iframe> </div> </div>