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Data table What is the value of R2 - R2- (Round to two decimal places.pdf
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Data table What is the value of R 2 ? R 2 = (Round to two decimal places as needed.).
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Create a network diagram using a forward pass and reverse pass from the following table: Adapted from RMC 10th Edition Pass PMP Guide Value: 10 The earliest the project can finish is The earliest activity I can finish is The amount of float on task F is.
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Develop an EER model for the following situation: After completing a course in database systems, you have been hired as an intern by a Community Hospital. You were assigned in a team tasked to develop a database design for the hospital's software system project - a Hospital Management System. This system also considers the coronavirus COVID-19 pandemic situation and wants to have a special monitoring for COVID-19 patients. After conducting a series of interviews with a number of hospital administrators and employees, you have identified the following entity types for the EER Model: - EMPLOYEE - is any person employed in the hospital. Each employee has an EmployeeID (identifier), Name, and DateHired. There are different types of EMPLOYEES and these are: DOCTORS, NURSES, and there are also other types of employees in the hospital. But, an employee must belong to only one type where an employee cannot do to the job of an employee with different job type. - DOCTOR - is an EMPLOYEE in the hospital. A doctor has a LicenseNo attribute. - NURSE - is an EMPLOYEE in the hospital. CareLevel needs to be recorded for each nurse. - CARE_UNIT - is a care center or station within the hospital. Each CARE_UNIT has a UnitID (identifier), and a UnitName. - ROOM - is a room in a certain care unit. A ROOM has a RoomNo (identifier), RoomType, and RoomPrice. - BED - is a hospital bed that may be assigned to a patient that will be admitted to the hospital. A BED cannot exist without being assigned to a ROOM, so that a BED depends on the ROOM. A BED has a BedNo (identifier), and a BedType. - PATIENT - a person who is either admitted to the hospital, or not. With special consideration to the COVID-19 pandemic, the hospital has only two patient classifications as COVID patients, or NON_COVID patients. A patient must belong to only one classification. Each PATIENT has the following attributes: PatientID (identifier), PName (which is composed of FName, and LName), BirthDate, Gender, and ContactNo. - COVID - is a patient diagnosed with COVID-19 illness. For each COVID patient, the Status, ExistingCondition (can have many existing conditions), and TravelHistory is recorded. - NON_COVID - is a patient diagnosed with other illnesses which is not COVID-19. Each NON_COVID patient has an IllnessType attribute. - COVID_TEST - is a laboratory test given only to COVID patients. Each COVID_TEST has a TestID (identifier), and a Description. Your team also noted the following information about relationships among entities: An EMPLOYEE supervises many employees, or may not supervise at all. But an EMPLOYEE must be supervised by exactly one employee. A DOCTOR must treat as a minimum one PATIENT; while, a PATIENT is treated by one or more DOCTORS. Every time a doctor treats a patient, the TreatDate, TreatDetails (which is composed of Medicine and Dosage), TotalCharges, InsurancePaid, and AmountDue (which is computed by subtracting the Insurance Paid from the Total Charges) are recorded. .
Develop an EER model for the following situation- After completing a c.pdf
Develop an EER model for the following situation- After completing a c.pdf
BorisdFHFraserk
Determine whether the following are characteristics/examples of competitive and/or non- competitive enzyme inhibitors. Reduce enzyme activity A. Both competitive and non- competitive inhibitors Bind to the enzyme active site B. Competitive inhibitor Used in feedback inhibition C. Noncompetitive inhibition Alter the shape of the active site by binding elsewhere on the enzyme.
Determine whether the following are characteristics-examples of compet.pdf
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BorisdFHFraserk
Determine what the key terms refer to in the following study. A study was conducted in a local community to analyze which voters would be likely to vote and how on an upcoming bond. Statistic a. voted, didn't vote, voted Sample b. all eligible voters in the community Parameter c. the attendance of a single voter Population d. the number of eligible voters who actually plan to vote Data e. a group of voters in the community who voted, randomly selected Variable f. the number of eligible voters in the study who actually plan to vote.
Determine what the key terms refer to in the following study- A study.pdf
Determine what the key terms refer to in the following study- A study.pdf
BorisdFHFraserk
Determine the value of current assets? Determine the value of current assets from the information below: Additional Information: i. Stock on 31 December 2011 was valued at $12500 ii. Accrued salaries amounted to $500 . iii. Prepaid insurance amounted to $125 . iv. Office Equipment is to be depreciated at 20% per annum. v. Provision for doubtful debts at 5% of the debtors A / c is to be created..
Determine the value of current assets- Determine the value of current.pdf
Determine the value of current assets- Determine the value of current.pdf
BorisdFHFraserk
Describe the interpretation for all of the pulmonary function testings.
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Describe the interpretation for all of the pulmonary function testings.pdf
BorisdFHFraserk
Describe the complete pipeline in ML using programming through PyTorch. For this, you need to write code that performs linear regression using PyTorch on simulated data. Make sure you include training, testing and evaluation in your code. { "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" } }, "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "id": "V0RhNGmBjFWt" }, "outputs": [], "source": [ "import torch\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn" ] }, { "cell_type": "code", "source": [ "# Creating a function f(X) with a slope of -5\n", "X = torch.arange(-5, 5, 0.2).view(-1, 1)\n", "func = -5 * X" ], "metadata": { "id": "Vq4OWcCNjJFj" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# Plot the line in red with grids\n", "plt.plot(X.numpy(), func.numpy(), 'r', label='func')\n", "plt.xlabel('x')\n", "plt.ylabel('y')\n", "plt.legend()\n", "plt.grid('True', color='y')\n", "plt.show()" ], "metadata": { "id": "EFDhIKURjPbB" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# Adding Gaussian noise to the function f(X) and saving it in Y\n", "Y = func + 1.7 * torch.randn(X.size())" ], "metadata": { "id": "c2KRcFl5jRuy" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# Plot and visualizing the data points in blue\n", "plt.plot(X.numpy(), Y.numpy(), 'b+', label='Y')\n", "plt.plot(X.numpy(), func.numpy(), 'r', label='func')\n", "plt.xlabel('x')\n", "plt.ylabel('y')\n", "plt.legend()\n", "plt.grid('True', color='y')\n", "plt.show()" ], "metadata": { "id": "ahd47p24jgrB" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# defining the function for forward pass for prediction\n", "def forward(x):\n", " return w * x" ], "metadata": { "id": "T-vtFS9Gjig2" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# evaluating data points with Mean Square Error.\n", "def criterion(y_pred, y):\n", " return torch.mean( (y_pred - y) ** 2 )" ], "metadata": { "id": "DpPaj2Vvjv5A" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "w = torch.tensor(-10.0, requires_grad=True)" ], "metadata": { "id": "UMXfOHC0jx9G" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "step_size = 0.1\n", "loss_list = []\n", "iter = 20" ], "metadata": { "id": "Ml6UCAqujzvm" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "for i in range (iter):\n", " # making predictions with forward pass\n", " Y_pred = forward(X)\n", "\n", "\n", " # calculating the loss between original and predicted data points\n", " loss = criterion(Y_pred, Y)\n", "\n", "\n", " # storing the calculated loss in a list\n", " loss_list.append(loss.item())\n", "\n", "\n", " # backward pass for .
Describe the complete pipeline in ML using programming through PyTorch.pdf
Describe the complete pipeline in ML using programming through PyTorch.pdf
BorisdFHFraserk
Detail view on the Product planning process and its 5 steps. 1. Identify opportunities 2. Evaluate and prioritize projects 3. Allocate resources and plan timing 4. Complete pre-project planning 5. Reflect on the results and the process. An detail answer with atleast 1000 words..
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Detail view on the Product planning process and its 5 steps- 1- Identi.pdf
BorisdFHFraserk
Determine the amount of the late filing and late payment penalties that apply for the following taxpayers. Required: o. Jolene filed her tax retum by its original due date but did not pay the $2 , 300 in taxes she owed with the return until one and a half months later. b. Oscar filed his tax return and paid his $3.300 tax llability five months late. c. Wilfred, attempting to evade his taxes, did not file a tax return or pay his $12.800 in taxes for several years..
Determine the amount of the late filing and late payment penalties tha.pdf
Determine the amount of the late filing and late payment penalties tha.pdf
BorisdFHFraserk
Determine the expenses for August based on the following data. (Click on the icon to view the data.) Data for August The expenses for August are.
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Determine the expenses for August based on the following data- (Click.pdf
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Data table What
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