http://liftothers.org/dokuwiki/ 2026-04-25T21:50:39+00:00 http://liftothers.org/dokuwiki/ http://liftothers.org/dokuwiki/lib/tpl/dokuwiki/images/favicon.ico text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_dla3&rev=1625096528&do=diff Literacy Assignment 3: Greenhouse Gases Data source: NY Times Article Objective: To think creatively and critically about data visualization decisions and motivation. ---------- Deliverable: 1 one-page PDF (no MSWORD, please!) writeup that responds to the questions below. text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_dla4&rev=1625096528&do=diff Literacy Assignment 4: Market Share Trends Data source: NY Times Article Objective: To think creatively and critically about data visualization decisions and motivation. Additionally, to use visualizations and data to spark further research and questions. ---------- text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_dla5&rev=1625096528&do=diff Literacy Assignment 5: Star Brightness Data source: Twitter Objective: To think creatively and critically about data visualization decisions and motivation. Additionally, to use visualizations and data to spark further research and questions. ---------- text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_dla6&rev=1625096528&do=diff Literacy Assignment 6: Movie Rating and Profit Data source: Book Objective: To think creatively and critically about data visualization decisions and motivation. Additionally, to use visualizations and data to spark further research and questions. ---------- text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_dla7&rev=1625096528&do=diff Literacy Assignment 7: Engagement Rings Data source: NY Times Article Objective: To think creatively and critically about data visualization decisions and motivation. Additionally, to use visualizations and data to spark further research and questions. ---------- text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_dla8&rev=1625096528&do=diff Literacy Assignment 8: Ride Hailing Data source: NY Times Article Objective: To think creatively and critically about data visualization decisions and motivation. Additionally, to use visualizations and data to spark further research and questions. ---------- Deliverable: text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_dla9&rev=1625096528&do=diff Literacy Assignment 9: Social Connectedness in America Data source: NY Times Article Objective: To think creatively and critically about data visualization decisions and motivation. Additionally, to use visualizations and data to spark further research and questions. text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_final&rev=1625096528&do=diff Objective: To creatively apply knowledge gained through the course of the semester to a substantial data science problem. ---------- Deliverable: You must turn in a PDF writeup of your project. The writeup must be about 6 pages long (including figures). text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_lab1&rev=1625096527&do=diff Literacy Lab 1: Nutrition Analysis: This is your first literacy lab! The goal is to start thinking about how to interpret data. Objective: To begin to think creatively and critically about data visualizations and analysis. ---------- Deliverable: text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_lab2&rev=1625096528&do=diff Literacy Lab 2: Tweet Sentiment: Now that 2020 is behind us, we can all breathe a collective sigh of relief and start sciencing it. Objective: To begin to think creatively and critically about data visualizations and analysis. ---------- Deliverable: text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs180_w2021&rev=1625096527&do=diff Welcome to CS201R, Winter 2021! The goal of this course is to give students a broad, introductory look at the field of data science. It will develop technical skills (including some python programming, statistics, machine learning, data cleaning and visualization) as well as broad data literacy (mental frameworks for decomposing data science problems, critical thinking about potential conclusions of an analysis, and potential pitfalls of overreliance on unreliable data). text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs330_f2016&rev=1625096526&do=diff Welcome to CS330, Fall 2016! Basic information about turning in labs, and using our Docker environments: Turning in assignments ---------- Labs Functional Programming in Racket Lab 1 - Racket Basics Lab 2 - Racket Lists and Recursion Lab 3 - Racket Higher-Order Functions Lab 4 - More Higher-Order Functions ---------- Julia Lab 5 - Julia Programming ---------- Simple Interpreters Lab 6 - Rudimentary Interpreter Lab 7 - Extended Interpreter Lab 8 - Program Analysis and Transformat… text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs330_f2017&rev=1625096526&do=diff Welcome to CS330, Winter 2020! Basic information and general resources: Turning in assignments Julia Resources and Help ---------- Labs Functional Programming in Racket Lab 1 - Racket Basics Lab 2 - Racket Lists and Recursion Lab 3 - Racket Higher-Order Functions Lab 4 - More Higher-Order Functions ---------- Simple Interpreters Lab 6 - Rudimentary Interpreter Lab 7 - Extended Interpreter Lab 8 - Program Analysis and Transformation Interpreter ---------- Prolog Lab 10 - Intro t… text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs330_w2017&rev=1625096526&do=diff Welcome to CS330, Winter 2017! Basic information and general resources: Turning in assignments Julia Resources and Help ---------- Labs Functional Programming in Racket Lab 1 - Racket Basics Lab 2 - Racket Lists and Recursion Lab 3 - Racket Higher-Order Functions Lab 4 - More Higher-Order Functions ---------- Julia Lab 5 - Julia Programming ---------- Simple Interpreters Lab 6 - Rudimentary Interpreter Lab 7 - Extended Interpreter Lab 8 - Program Analysis and Transformation Int… text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs330_w2018&rev=1625096527&do=diff Welcome to CS330, Winter 2018! Basic information and general resources: Turning in assignments Julia Resources and Help ---------- Labs Functional Programming in Racket Lab 1 - Racket Basics Lab 2 - Racket Lists and Recursion Lab 3 - Racket Higher-Order Functions Lab 4 - More Higher-Order Functions ---------- Simple Interpreters Lab 5 - Rudimentary Interpreter Lab 6 - Extended Interpreter Lab 7 - Program Analysis and Transformation Interpreter ---------- Prolog Lab 8 - Intro to… text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs401r_w2016&rev=1625096526&do=diff Winter 2016 - CS401r - Modern Data Analysis with Statistical ML Labs General notes on ipython and seaborn Lab 1 - Anaconda and pandas Lab 2 - Bayesian concept learning Lab 3 - MNIST with KDE Lab 4 - Gaussian process regression Lab 5 - Large-scale Gaussian process regression Lab 6 - Expectation maximization Lab 7 - Kalman filter Lab 8 - Localization with particle filters Lab 9 - LDA, General Conference, and Gibbs sampling Lab 10 - Metropolis Hastings and Hamiltonian MCMC Lab 11 - Rec… text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs401r_w2017&rev=1625096526&do=diff Winter 2017 - CS401r - Modern Data Analysis with Statistical ML ---------- Resources General notes on ipython and seaborn You should become intimately familiar with numpy's broadcasting ---------- Labs Lab 1 - Anaconda and pandas Lab 2 - Bayesian concept learning Lab 3 - MNIST with KDE Lab 4 - Gaussian process regression Lab 5 - Large-scale Gaussian process regression Lab 6 - Expectation maximization Lab 7 - Kalman filter Lab 8 - Localization with particle filters Lab 9 - LDA, Gen… text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs401r_w2018&rev=1625096527&do=diff Winter 2018 - CS401r - Modern Data Analysis with Statistical ML ---------- Resources General notes on ipython and seaborn You should become intimately familiar with numpy's broadcasting ---------- Labs Lab 1 - Anaconda and pandas Lab 2 - Bayesian concept learning Lab 3 - MNIST with KDE Lab 4 - Gaussian process regression Lab 5 - Large-scale Gaussian process regression Lab 6 - Expectation maximization Lab 7 - Kalman filter Lab 8 - Localization with particle filters Lab 9 - LDA, Gen… text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs474_f2020&rev=1625096527&do=diff Welcome to CS474, Fall 2020! Welcome to the most exciting class on campus! We will study the basics of deep neural networks (DNNs), including high-level philosophy, basic mathematics and models, training, initialization, and regularization; common usages such as classification, regression, reinforcement learning and generative models; interesting applications like style/content transfer, language translation, audio processing, language and image synthesis/generation, and control; as well as m… text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs474_f2020_projects&rev=1625096527&do=diff Final project: There are 10 programming projects in this course, plus a final project. These projects are all hosted on Github at <https://github.com/wingated/cs474_labs> This page describes the final project. Objective: To creatively apply knowledge gained through the course of the semester to a substantial learning problem of your own choosing. text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs501r_f2016&rev=1625096526&do=diff CS501r, Fall 2016 - Deep Learning: Theory and Practice Here is the course description. Remember, this is a great tutorial on python / numpy! Some instructions for getting Tensorflow to run on the CS open labs All of the slides are posted on Dropbox here ---------- Labs General notes on ipython and seaborn Lab 1 - Anaconda and playground screenshot Lab 2 - Perceptron Lab 3 - Basic gradient descent Lab 4 - Automatic differentiation Lab 5 - Tensorflow image classifier Lab 5b - Convolut… text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs501r_f2016_desc&rev=1625096526&do=diff CS501r, Fall 2016 - Deep Learning: Theory and Practice As big data and deep learning gain more prominence in both industry and academia, the time seems ripe for a class focused exclusively on the theory and practice of deep learning, both to understand why deep learning has had such a tremendous impact across so many disciplines, and also to spur research excellence in deep learning at BYU. text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs501r_f2017&rev=1625096526&do=diff CS501r, Fall 2017 - Deep Learning: Theory and Practice Here is the course description. Remember, this is a great tutorial on python / numpy! Some instructions for getting Tensorflow to run on the CS open labs All of the slides are posted on Dropbox here A quick intro to deep learning on the supercomputer A quick intro to deep learning on google cloud A nice tutorial on setting up wsl for machine learning ---------- Labs General notes on ipython and seaborn Lab 1 - Anaconda and playgro… text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs501r_f2018&rev=1625096527&do=diff CS501r, Fall 2018 - Deep Learning: Theory and Practice Here is the course description. All of the slides are posted on Dropbox here ---------- Labs Lab 1 - Colab and playground screenshot Lab 2 - Get to know pytorch Lab 3 - Your first DNN Lab 4 - Cancer Detection Lab 5 - Style Transfer Lab 6 - Unreasonable Effectiveness of RNNs Lab 7 - Attention Is All You Need Lab 8 - Improved Wasserstein GAN Lab 9 - Deep RL & PPO ...More labs will be added here... Final project ---------- … text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs601r_w2020&rev=1625096527&do=diff Welcome to CS601R, Winter 2020! ---------- Labs Lab 1 - Basic classifier Lab 2 - Hyper Zoo ---------- Projects and Proposals Project proposals Project 1 and 2 Final project text/html 2021-06-30T23:42:08+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs674_w2021&rev=1625096528&do=diff Welcome to CS674, Winter 2021! ---------- Labs Lab 1 - Basic classifier Lab 2 - Hyper Zoo ---------- Projects and Proposals Project proposals Project 1 and 2 Final project text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=cs704r_w2019&rev=1625096527&do=diff Applications * BERT - <https://arxiv.org/abs/1810.04805> * Machine Theory of Mind - <http://arxiv.org/pdf/1802.07740v2.pdf> * Video-to-Video Synthesis * Video Prediction via Selective Sampling * Learning to decompose & disadvantage representations for video prediction GANs / unsupervised * Composing graphical models with neural networks for structured representations and fast inference text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=googlecloud&rev=1625096527&do=diff Deep Learning on the Google Cloud Platform Installing gcloud on a local machine 1. Install gcloud sdk on your local machine (I personally used window linux subsystem, therefore I chose the apt-get option) reference: <https://cloud.google.com/sdk/downloads> 2. Use the following code to setup user account, including setting region of computation unit. text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=old_versions&rev=1625096527&do=diff Older versions of classes Fall 2020 - CS474 - Deep Learning: Theory and Practice Winter 2020 - CS330 - Concepts of Programming Languages Winter 2020 - CS601R - Advanced Deep Learning Fall 2018 - CS501r - Deep Learning: Theory and Practice Fall 2017 - CS501r - Deep Learning: Theory and Practice Winter 2017 - CS330 - Concepts of Programming Languages Winter 2017 - CS401r - Modern Data Analysis with Statistical ML Fall 2016 - CS330 - Concepts of Programming Languages Fall 2016 - CS501r - D… text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=pccl&rev=1625096526&do=diff Stuff to read: Visualizing representations Unreasonable effectiveness of RNNs Deepmind paper on DNNs and Atari Inceptionism Everything on the Deepmind publications page Neural networks and deep learning - online book text/html 2021-06-30T23:42:06+00:00 http://liftothers.org/dokuwiki/doku.php?id=start&rev=1625096526&do=diff Courses Winter 2021 - CS201R - Introduction to Data Science Winter 2021 - CS674 - Advanced Deep Learning Misc Older stuff text/html 2021-06-30T23:42:07+00:00 http://liftothers.org/dokuwiki/doku.php?id=supercomputer&rev=1625096527&do=diff Deep Learning on the Supercomputer Setting Up Supercomputer To get started on the supercomputer you need to follow the instructions and get an account from <https://marylou.byu.edu/>. Once you have this set up you can SSH in with ssh <username>@ssh.fsl.byu.edu Welcome to our new home directory. Using the supercomputer means we have to remember elementary school and be nice and share. This means we can only used software that is approved and stored in