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When & Where
Date: 
Wed, April 29, 2020 - 1:00 PM to 4:00 PM
Location: 
Remote (Zoom link below)
Description
Type: 
Zoom Link
To obtain the Zoom link for this workshop please click the link below:
 
 
After re-registering on the Zoom website, you will receive a confirmation email containing information about joining the meeting.
 
If you already have and use a Zoom account, please sign into it first before trying to access the D-Lab workshop.
 
If you have questions or problems with Zoom, please email: dlab-frontdesk@berkeley.edu
 
Overview
  1.  A brief history of ANNs and an explanation of the intuition behind them. This part aims to give the audience a conceptual understanding with few mathematical barriers, and no programming requirements.
  2. Step-by-step construction of a very basic ANN. Although the code will be written in Python, it will be intuitive enough for programmers of other languages to follow along. 
  3. Using the popular Python library scikit-learn, an ANN will be implemented on a classification problem. High-level libraries reduce the work for a researcher implementing ANN down to tuning a set of parameters, which will be explained in this part.

Prior knowledge: D-Lab's Python for Everything or R Fundamentals and an interest in machine learning.

Technology requirement: To follow along in parts 2 and 3, it is suggested to install Python via Anaconda. Instructions can be found here.

Primary Tool: 
Python
Details
Training Learner Level: 
Basic Competency
Training Host: 
D-lab Facilitator: 
Evan Muzzall
Format Detail: 
Remote, hands-on, interactive
Participant Technology Requirement: 
Laptop, Internet Connection, Zoom account
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