class: center, middle, inverse, title-slide # Wrap up ### Brad Boehmke ### 2020-01-27 --- class: inverse, center, middle # You've learned a lot! --- # Modeling purposes .font130[ .pull-left[ .bold[Covered:] ☒ Regression ☒ Classification ☒ Computer vision ☒ Recommendation systems ☒ NLP processing & classification ] .pull-right[ .bold[Not covered:] ☐ Language modeling ☐ Time series analysis ☐ Anomaly detection ☐ Object detection/tracking ☐ Video classification ☐ and more! ] ] --- # Model architectures .font130[ .pull-left[ .bold[Covered:] ☒ MLPs ☒ CNNs ☒ Embeddings ☒ RNNs ☒ LSTMs ☒ Transfer learning ] .pull-right[ .bold[Not covered:] ☐ Autoencoders ☐ Reinforcement learning ☐ Generative adversarial networks ☐ Natural language models ☐ Alternative (CNN, RNN, embedding, ...) architectures ] ] --- # Model gears .font130[ .pull-left[ .bold[Covered:] ☒ Tensors ☒ Sequential vs functional models ☒ Activation functions ☒ Derivatives ☒ Backward propagation ☒ Batches & epochs ☒ Learning rate ☒ Various types of layers ☒ and more! ] .pull-right[ .bold[Not covered:] ☐ Batch normalization ☐ Gradient clipping ☐ Greedy layer-wise pretraining ☐ Alternative learning rate schedules ☐ Alternative optimizers ☐ Alternative callbacks ☐ Attention mechanisms ☐ Flags for grid searches ☐ and more! ] ] --- class: inverse, center <br><br><br><br><br> # You now have the fundamentals knowledge to learn these more advanced features...<br> --- class: inverse, center <br><br><br><br><br> # You now have the fundamentals knowledge to learn these more advanced features...<br><br>So what next <span style=" display: -moz-inline-stack; display: inline-block; transform: rotate(0deg);"><img src="https://emojis.slackmojis.com/emojis/images/1542340471/4979/thinking.gif?1542340471" style="height:1em; width:auto; "/></span> --- # Immediate pain .pull-left[ .bold[Give the final project a try] <img src="images/quora_icon.png" width="1299" /> ] -- .pull-right[ .bold[Check out some of the extra notebooks] <img src="images/extra-notebooks.png" width="976" /> ] --- # Books .pull-left[ .bold[Start with...] * [Deep Learning with R](https://www.amazon.com/Deep-Learning-R-Francois-Chollet/dp/161729554X/ref=sr_1_3?keywords=Deep+learning+with+r&qid=1578497534&sr=8-3) * [Deep Learning with R in Motion](https://www.manning.com/livevideo/deep-learning-with-r-in-motion) * [Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow](https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_2?keywords=Hands-On+Machine+Learning+with+Scikit-Learn%2C+Keras%2C+and+TensorFlow&qid=1578497554&sr=8-2) * [Better Deep Learning](https://machinelearningmastery.com/better-deep-learning/) * [Deep Learning for Computer Vision](https://www.pyimagesearch.com/deep-learning-computer-vision-python-book/) * [Deep Learning](http://www.deeplearningbook.org/) (theoretical) ] .pull-right[ <br><br><br><br> .bold.center[These books will point you to other books to read later] ] --- # Online resources .font130.pull-left[ .bold[Online courses:] * [fast.ai](https://www.fast.ai/) - Practical Deep Learning for Coders - Deep Learning from the Foundations - Code-first Introduction to Natural Language Processing * [Andrew Ng's Deep Learning course](https://www.coursera.org/specializations/deep-learning?edocomorp=mar19affiliate20off&ranMID=40328&ranEAID=vedj0cWlu2Y&ranSiteID=vedj0cWlu2Y-B5mQGmLDcZfcJrMEYdAdGA&siteID=vedj0cWlu2Y-B5mQGmLDcZfcJrMEYdAdGA&utm_content=10&utm_medium=partners&utm_source=linkshare&utm_campaign=vedj0cWlu2Y) * [Deep Learning with R in Motion](https://www.manning.com/livevideo/deep-learning-with-r-in-motion) ] .font130.pull-right[ .bold[Other:] * https://tensorflow.rstudio.com/ * https://keras.rstudio.com/ * https://community.rstudio.com/ * https://www.pyimagesearch.com/ ] --- class: inverse # Stay in touch! .font150.white.pull-right-wide[ <br><br> [<svg style="height:0.8em;top:.04em;position:relative;fill:white;" viewBox="0 0 496 512"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"/></svg>](http://bradleyboehmke.github.io/) bradleyboehmke.github.io <br> [<svg style="height:0.8em;top:.04em;position:relative;fill:white;" viewBox="0 0 496 512"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>](https://github.com/bradleyboehmke/) @bradleyboehmke <br> [<svg style="height:0.8em;top:.04em;position:relative;fill:white;" viewBox="0 0 512 512"><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>](https://twitter.com/bradleyboehmke) @bradleyboehmke <br> [<svg style="height:0.8em;top:.04em;position:relative;fill:white;" viewBox="0 0 512 512"><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg>](mailto:bradleyboehmke@gmail.com) bradleyboehmke@gmail.com ] --- # .center.font120[[rstd.io/ws-survey](http://rstd.io/ws-survey)] <img src="https://d2dfxqxblmblx4.cloudfront.net/wp-content/uploads/2016/03/18151100/Survey-2-1024x1024.jpg" width="45%" height="45%" style="display: block; margin: auto;" /> --- # Back home <br><br><br><br> [.center[<span><i class="fas fa-home fa-10x faa-FALSE animated "></i></span>]](https://github.com/rstudio-conf-2020/dl-keras-tf) .center[https://github.com/rstudio-conf-2020/dl-keras-tf]