It is a privilege to use lasers at Stanford University. It is important here at the outset that we draw attention to a distinction between desert and another concept with which it might be confused. Keras Tutorial: This assignment is optional. Special note to Stanford researchers: Except for regulated data such as Protected Health Information (PHI), Social Security Numbers (SSNs), and financial account numbers, research data and systems predominately fall into the Low Risk classification. The Computer Science major offers a number of tracks (programs of study) from which students can choose, allowing them to … If you’re interested in testing your ML/DL skills or preparing for job interviews in AI, you can take the Workera assessment; Project Meeting #3: 03/18 Thursday 11:59 PM: Instructions: Meet with your assigned TA between 2/27 and 3/18 (before class) to discuss your final project report. The loss of confidentiality, integrity, or availability of the data or system could have a mildly adverse impact on our mission, safety, finances, or reputation. The loss of confidentiality, integrity, or availability of the data or system could have a significant adverse impact on our mission, safety, finances, or reputation. Research data (at data owner's discretion), Information authorized to be available on or through Stanford's website without SUNet ID authentication, Policy and procedure manuals designated by the owner as public, University contact information not designated by the individual as "private" in StanfordYou, Unpublished research data (at data owner's discretion), Student records and admission applications, Faculty/staff employment applications, personnel files, benefits, salary, birth date, personal contact information, Non-public Stanford policies and policy manuals, Stanford internal memos and email, non-public reports, budgets, plans, financial info, Engineering, design, and operational information regarding Stanford infrastructure, Health Information, including Protected Health Information (PHI), Donor contact information and non-public gift information, Servers used for research computing purposes without involving Moderate or High Risk Data, File server used to store published public data, Database server containing SUNet IDs only, Database of non-public University contracts, File server containing non-public procedures/documentation, Servers managing access to High Risk systems, University IT and departmental email systems, University online catalog displaying academic course descriptions, Human Resources application that stores salary information, Directory containing phone numbers, email addresses, and titles, University application that distributes information in the event of a campus emergency, Online application for student admissions, Human Resources application that stores employee SSNs, Application that stores campus network node information, Application collecting personal information of donor, alumnus, or other individual, Application that processes credit card payments. Stanford is committed to protecting the privacy of its students, alumni, faculty and staff, as well as protecting the confidentiality, integrity, and availability of information important to the University's mission. All individuals who currently or will work with lasers are responsible for knowing and adhering to applicable requirements as stated in this manual. Linear Classification In the last section we introduced the problem of Image Classification, which is the task of assigning a single label to an image from a fixed set of categories. See Research Policy Handbook Section 1.10 for information security practices and guidelines specific to research computing systems. Watch Information Security Awareness Video, Administrative Guide: Information Security, Audio and Video Conferencing: Zoom and WebEx, Google G Suite: Docs, Sheets, Forms and Slides, Google G Suite: All others (Sites, Photos, etc...), Smartsheet: Collaboration and Project Management, Survey Tool: Qualtrics - University, SoM, and GSB instances, Survey Tool: Qualtrics - All other instances, Stanford Research Computing Center (SRCC), Technology Toolkit for Telecommuting and Remote Work, The data is intended for public disclosure, or. In 1972, affirmative action became an inflammatory public issue. 1. Review the classification definitions and examples below to determine the appropriate risk level to apply. The data is not generally available to the public, or. online Facilities Service Request; pdf Salvage Form To be used with ESH Radiological Survey. The current scoring method for all IQ tests is the "deviation IQ". You'll train a binary classifier to perform sentiment analysis on an IMDB dataset. Thur 8:30 AM - 9:50 AM Zoom (access via "Zoom" tab of Canvas). Special Applications: Face Recognition & Neural Style Transfer, Art Generation with Neural Style Transfer, Building a Recurrent Neural Network - Step by Step, Dinosaur Land -- Character-level Language Modeling, C5M2: Natural Language Processing and Word Embeddings, Natural Language Processing and Word Embeddings, Neural Machine Translation with Attention, If youâre interested in testing your ML/DL skills or preparing for job interviews in AI, you can take the. The loss of confidentiality, integrity, or availability of the data or system would have no adverse impact on our mission, safety, finances, or reputation. This table indicates which classifications of data are allowed on a selection of commonly used Stanford University IT services. Data and systems are classified as Low Risk if they are not considered to be Moderate or High Risk, and: Data and systems are classified as Moderate Risk if they are not considered to be High Risk, and: Data and systems are classified as High Risk if: Use the examples below to determine which risk classification is appropriate for a particular type of data. Logistic Regression with a neural network mindset, Planar data classification with a hidden layer, Building your Deep Neural Network: step by step, Attacking neural networks with Adversarial Examples and Generative Adversarial Networks, C2M3: Hyperparameter Tuning, Batch Normalization, Hyperparameter tuning, Batch Normalization, Programming Frameworks, Bird recognition in the city of Peacetopia (case study), C4M1: Foundations of Convolutional Neural Network. Review the classification definitions and examples below to determine the appropriate risk level to apply. The former framework — Prohibited, Restricted, Confidential, and Unrestricted — was phased out in January 2016. A server is defined as a host that provides a network accessible service. Stanford has classified its information assets into risk-based categories for the purpose of determining who is allowed to access the information and what security precautions must be taken to protect it against unauthorized access. Copyright © 2021. Desert and Entitlement. The department offers both a major in Computer Science and a minor in Computer Science. Protection of the data is required by law/regulation, Stanford is required to self-report to the government and/or provide notice to the individual if the data is inappropriately accessed, or. Non-ESH Forms. Visualizing and Understanding Convolutional Networks, Deep Inside Convolutional Networks: Visualizing Image Classification Models and Saliency Maps, Understanding Neural Networks Through Deep Visualization, Learning Deep Features for Discriminative Localization, Dropout: A Simple Way to Prevent Neural Networks from Overfitting, DenseNet: Densely Connected Convolutional Networks, Human-level control through deep reinforcement learning, Mastering the Game of Go without Human Knowledge. If you are enrolled in CS230, you will receive an email on 01/13 to join Course 1 ("Neural Networks and Deep Learning") on Coursera with your Stanford email. When mixed data falls into multiple risk categories, use the highest risk classification across all. If Salvage is Radioactive, use with Radioactive Material Declaration Form More information at SCM Property Control: Surplus; ESH General Forms Project ESH Review Process This tutorial demonstrates text classification starting from plain text files stored on disk. Is the deconvolution layer the same as a convolutional layer?
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