Grading Rubric For C++
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The grading rubric for a C++ programming assignment totals 100 points and evaluates submissions based on specifications (60 points), readability (10 points), reusability (5 points), documentation (10 points), delivery/timeliness (up to 15 points off for late submissions), and efficiency (15 points). The specifications criteria focuses on the program working correctly and meeting all requirements, while efficiency considers optimized code without sacrificing readability or error handling.
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Let's review it: What designers can learn from (code) review
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This document provides information about the CSCI 1100: Introduction to Personal Computing course for the Fall 2008 semester. It outlines details such as the instructor's name and contact information, class times and location, course objectives to teach basic computer skills, required textbook and software, grading structure which includes assignments, exams and a class webpage project, and policies regarding withdrawals, disabilities, and academic honesty.
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Sriti Kumar is a professor in the Department of Computer Science at the University of Georgia. In her statement of teaching philosophy, she believes students learn best through an active approach where they interact more in class through discussions, group activities, assignments, and projects. She wants students to not only learn course materials but also share their knowledge with others. Her main goal is to help students become independent critical thinkers by making them understand concepts and providing feedback to help them improve.
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Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
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- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
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- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
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- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
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12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
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Grading Rubric For C++
- 1. Grading Rubric for C++ Programming Assignment Total Score: 100 For the code submission make sure that there is a tagged version if your repository that we can clearly identify as the final submission. Please don't call your folders FinalSubmission1, FinalSubmission2, etc. Make one that we can quickly eyeball as the final submission. The grading will be based on the following criteria: 1. Specifications - 60 Points The program works and puts corrects output. Meet all the specifications. 2. Readability - 10 Points Organization Readability 3. Reusability - 5 Points The code could be reused as a whole or each routine could be reused. 4. Documentation – 10 Points The documentation consists of embedded comment and some simple header documentation that is somewhat useful in understanding the code. 5. Delivery When the assignment was submitted. If you have submitted after one day then you will be graded out of 90 and then on subsequent days score will decrease by 25% everyday. 6. Efficiency – 15 Points The code is extremely efficient without sacrificing readability and understanding. Also taking into consideration all wrong inputs. If you have any doubts please send me an email. In every program I make some test cases which I will be putting up after the submission date. Sriti Kumar