The subject for the first of three larger written assignments in the course is the interaction between Congress and the Executive branches, topics from Modules 4-6.  ASSIGNMENT OVERVIEW A recent presidential election, new Administration, unified government, and renewed interest in separation of powers between co-equal branches, executive authority over the bureaucracy, the role of congressional oversight all point to a relevant range of subjects for […]

Submit a 250-word summary of your class notes here. Your notes should NOT be a word-for-word transcription of what you find in this section. Instead, your notes must:  Address key terms or topics that came up in the course module. Explain how you think the assigned readings tie-in. Make sure to include the primary reading! Provide two links to reputable sites that clarify, extend, or correct something […]

   A process recording is a written tool used by field education experience students, field instructors, and faculty to examine the dynamics of social work interactions in time. Process recordings can help in developing and refining interviewing and intervention skills. By conceptualizing and organizing ongoing activities with social work clients, you are able to clarify the purpose of interviews and interventions, identify personal and professional […]

   Prompt: Drawing on the work of Gutiérrez and Lorde, make an argument for how solidarity can be a starting point for saying something true about God. You are encouraged to make use of the Writing Resource Center to improve your writing. Format: Times New Roman, 12-point, 1-inch margins 3 pages, double-spaced Because you’re only using sources we’ve read in this course, you can cite […]

On the Discussion Board we will be exploring conceptual models.Hamric’s Integrative Model of Advance Practice NursingThe AACN Synergy ModelStrong Memorial Hospital’s Model of Advance Practice NursingShuler’s Model of Nurse Practitioner PracticeThis week you will describe how these models may help APNs articulate professional role identify and function. Conceptual models will serve as a framework for organizing beliefs and knowledge about your professional roles and competencies […]

  Analysis The principles of unity & variety apply to all music, regardless of compositional style or historical period. Now that you are familiar with the concepts in the first section of the course (Basic Musical Concepts), and you have seen how they work on different pieces of music, try your hand, mouse, and ears at how they operate in a music selection that you […]

  Week 3 Project       Individual Assignment: Group Case Study Project:   Each week, as you consider the Crocs: Revolutionizing an Industry’s Supply Chain Model for Competitive Advantage case study, you will have two Group Project assignments to complete. One will involve a Group Discussion and the other will be an Individual Assignment. The information from both parts will be used for your final Group Case […]

DETAILED PAPER DIRECTIONS: THE SCIENCE AND EVOLUTION OF MORALITY You will watch three videos–one about morality in babies–and the other two about morality in animals. The big topic here is the evolutionary origin of our moral emotions. Where does morality come from? The assignment is as follows. First, you will write a paragraph introducing the topic. Then you will write at least a page-and-a-half summarizing […]

Create jupyter notebook file: Intro_NN_XORGATE.ipynb ****Exercise**** # Uncomment the xor_gate line and find out which neurons besides the or_gate neuron the# network should have in its hidden and output layer to produce the right values. in[]class Network():def __init__(self, gate1, gate2, out_gate):self.hidden_neuron1 = gate1self.hidden_neuron2 = gate2self.out_neuron = out_gatedef activate(self, x1, x2):z1 = self.hidden_neuron1.activate(x1, x2)z2 = self.hidden_neuron2.activate(x1, x2)return self.out_neuron.activate(z1, z2)#xor_gate = Network(…, …, and_gate)make_truth_table(xor_gate) ****Exercise**** # Finish […]

USE Jupyter Notebook NB: Please only do Tasks 1-2 We will combine what we’ve learned about convolution, max-pooling and feed-forward layers, to build a ConvNet classifier for images. Given Code: in[]from __future__ import absolute_import, division, print_function # Prerequisits!pip install pydot_ng!pip install graphviz!apt install graphviz > /dev/null # import statementsimport tensorflow as tfimport tensorflow.contrib.eager as tfeimport numpy as npimport matplotlib.pyplot as pltfrom IPython import display%matplotlib inline […]