Welcome to Noel’s Workshop Pages
Spring 2018 Workshops
This is where the descriptions of the workshops will be uploaded
Feb 05 11:00 AM ‖ MacLab 424
Kickstart your software engineer career with a star profile on GitHub. Come to this workshop to learn the basics of git versioning, as well as to learn some tips on building your portfolio. You will be working in groups to simulate versioning problems. In this workshop, you will learn how to create a repository, start and manage branches, merge pull requests, write a basic markdown file, and how to be social on GitHub!
TensorFlow: The Basics
Mar 12 3:30 PM ‖ MacLab 424
TensorFlow is crucial in building neural networks faster. However, the basics of TensorFlow may be confusing as building, training, testing models aren’t that straightforward. Come to this session to learn about placeholders, variables, graphs, and sessions. In the end, we will build a rudimentary regression model to put into practice your knowledge of TensorFlow. This workshop is the first of the TensorFlow workshop series in which Deep Neural Networks and Recurrent Neural Networks will be explored. The Basics workshop lays down the foundation for the subsequent two workshops.
TensorFlow Basics: Simple Regression
TensorFlow: Wide & Deep Learning
Mar 14 3:30 PM ‖ MacLab 504
In this workshop, you will learn learn two Estimator APIs. The first part of the workshop will focus on
LinearRegressor and the
DNNLinearCombinedClassifier With a Wide and Deep Neural Network, you will be able to perform classification and regression tasks. The skills you will learn through this workshop include the following. You will be able to create feature columns (numerical, categorical with hash bucket, bucketized) in TensorFlow, cross these columns if needed for the Wide Model, embed sparse feature columns into the Deep Model and combine them for a Wide & Deep Model.If you are interested in how Wide & Deep Learning works, read this research paper. For the second part of the workshop we will do a live coding competition, using the Pima Indians Diabetes Dataset to predict the occurrence of diabetes.
TensorFlow: The LinearRegressor API
TensorFlow: Wide & Deep Learning API
TensorFlow: Live Coding
TensorFlow: Recurrent Neural Networks
Mar 19 3:30 PM ‖ MacLab 424
This is a more advanced TensorFlow workshop. In the first 15 minutes, we will cover the building blocks of Recurrent Neural Networks (RNN). RNNs are typically used for time-series data prediction, as well as language modeling. The core feature of the model is that it feeds in the output from the previous state among the inputs to the new state, thus creating some degree of time-bound (or syntax relational) dependency. We will get started with a time-series dataset, which we will use to train our model to predict future steps. If you are interested in how RNNs work, read this excellent guide.
Business Analytics: Web Scraping Series
Web Scraping Part 1
Mar 09 1:30 PM - 3:00 PM ‖ MacLab 504
This is the first session of a data scraping workshops series for the Business Analytics class. Working with data in Python is not a rocket science, but also requires some foundational skills. To get the most out of this workshop, a stable understanding of Python is required, such as working knowledge of loops, being able to independently write functions, and a stable understanding of nested lists and matrices. Open the workshop page to learn about the resources for Data management in Python with Pandas. In this workshop, you will learn the basic functionalities of the Pandas library (think of it as Excel but faster and cooler), and you will also learn how to use Yelp API. If time permits, the third topic of the workshop is how to read and manage JSON files, which are typically the responses you get from API requests.
Web Scraping Part 1: Introduction to Pandas
Web Scraping Part 1: Using Yelp API to get JSON data
Web Scraping Part 1: Importing your JSON data into Pandas
Web Scraping Part 2
April 26 1:30 PM - 3:00 PM ‖ Location TBD
This workshop will delve deeper into understanding API requests, as well as methods for retrieving JSON data when there are no publicly available APIs with the use case of collecting flight price data from the English site of Ctrip. We will use Postman to intercept automatic API requests that our browser makes. This workshop assumes you are comfortable using Pandas, as well as you have some knowledge of APIs. You may want to recap the last workshop’s materials through the online workshop videos.