Download or read book The C Workshop written by Charles Pine and published by . This book was released on 1992-03 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pic C written by Nigel Gardner and published by . This book was released on 1998 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vocabulary Workshop written by Jerome Shostak and published by William H. Sadler. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: It's a good book. Offers pronounciation, definitions, synonyms, and antonyms, as well as good practice. Chances are there are at least some words you'll learn from the book, even if you do well on the diagnostic test but I still suggest that you take that test to see if you should get a higher level book.

Download or read book Retooling for an Aging America written by Institute of Medicine and published by National Academies Press. This book was released on 2008-08-27 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the first of the nation's 78 million baby boomers begin reaching age 65 in 2011, they will face a health care workforce that is too small and woefully unprepared to meet their specific health needs. Retooling for an Aging America calls for bold initiatives starting immediately to train all health care providers in the basics of geriatric care and to prepare family members and other informal caregivers, who currently receive little or no training in how to tend to their aging loved ones. The book also recommends that Medicare, Medicaid, and other health plans pay higher rates to boost recruitment and retention of geriatric specialists and care aides. Educators and health professional groups can use Retooling for an Aging America to institute or increase formal education and training in geriatrics. Consumer groups can use the book to advocate for improving the care for older adults. Health care professional and occupational groups can use it to improve the quality of health care jobs.

Download or read book Sustainable Critical Infrastructure Systems written by National Research Council and published by National Academies Press. This book was released on 2009-07-01 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the people of the United States, the 20th century was one of unprecedented population growth, economic development, and improved quality of life. The critical infrastructure systems-water, wastewater, power, transportation, and telecommunications-built in the 20th century have become so much a part of modern life that they are taken for granted. By 2030, 60 million more Americans will expect these systems to deliver essential services. Large segments and components of the nation's critical infrastructure systems are now 50 to 100 years old, and their performance and condition are deteriorating. Improvements are clearly necessary. However, approaching infrastructure renewal by continuing to use the same processes, practices, technologies, and materials that were developed in the 20th century will likely yield the same results: increasing instances of service disruptions, higher operating and repair costs, and the possibility of catastrophic, cascading failures. If the nation is to meet some of the important challenges of the 21st century, a new paradigm for the renewal of critical infrastructure systems is needed. This book discusses the essential components of this new paradigm, and outlines a framework to ensure that ongoing activities, knowledge, and technologies can be aligned and leveraged to help meet multiple national objectives.

Download or read book The C Workshop written by Charles Pine and published by . This book was released on 1987 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vocabulary Workshop Level A Grade 6 written by Jerome Shostak and published by . This book was released on 1982 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Dreamworking written by Christopher Sowton and published by Llewellyn Worldwide. This book was released on 2017-03-08 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your dreams are trying to guide you, but do you understand what they’re saying? Dreamworking provides a practical process for connecting your dreams to your life, helping you understand the profound requests that come while you sleep. Join Christopher Sowton as he shares five steps to receiving the inner guidance of our dreams: Catch, Clarify, Orient, Connect, Respond. With hands-on techniques, examples from the author’s psychotherapy practice, and guidance for working with fourteen common dream motifs, this book shows how to facilitate dreamwork for psychological and spiritual transformation. Whether a dream wants you to take action, improve your understanding, or make a specific change, you can rest assured that it’s leading you to new perspectives and fulfilling resolutions. Praise: “Christopher Sowton has presented a book that is not only thoroughly original but incredibly comprehensive in both its width and its depth. If you apply the method so well articulated in Dreamworking, your life may never be the same again—and you will celebrate the change!” —Stanley Krippner, PhD, co-author of Extraordinary Dreams “In his excellent guidebook for helping people understand dreams, their own or those of clients, Dr. Christopher Sowton provides a precious map of the territory.”?—Patricia Garfield, PhD, author of Creative Dreaming

Download or read book The Complete Workshop Companion Series written by Nick Engler and published by . This book was released on 2015-06-23 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Your Code as a Crime Scene written by Adam Tornhill and published by Pragmatic Bookshelf. This book was released on 2015-03-30 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Jack the Ripper and legacy codebases have more in common than you'd think. Inspired by forensic psychology methods, you'll learn strategies to predict the future of your codebase, assess refactoring direction, and understand how your team influences the design. With its unique blend of forensic psychology and code analysis, this book arms you with the strategies you need, no matter what programming language you use. Software is a living entity that's constantly changing. To understand software systems, we need to know where they came from and how they evolved. By mining commit data and analyzing the history of your code, you can start fixes ahead of time to eliminate broken designs, maintenance issues, and team productivity bottlenecks. In this book, you'll learn forensic psychology techniques to successfully maintain your software. You'll create a geographic profile from your commit data to find hotspots, and apply temporal coupling concepts to uncover hidden relationships between unrelated areas in your code. You'll also measure the effectiveness of your code improvements. You'll learn how to apply these techniques on projects both large and small. For small projects, you'll get new insights into your design and how well the code fits your ideas. For large projects, you'll identify the good and the fragile parts. Large-scale development is also a social activity, and the team's dynamics influence code quality. That's why this book shows you how to uncover social biases when analyzing the evolution of your system. You'll use commit messages as eyewitness accounts to what is really happening in your code. Finally, you'll put it all together by tracking organizational problems in the code and finding out how to fix them. Come join the hunt for better code! What You Need: You need Java 6 and Python 2.7 to run the accompanying analysis tools. You also need Git to follow along with the examples.

Download or read book Workshop Math written by Robert Scharff and published by Sterling Publishing Company, Inc.. This book was released on 1989 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Workshop math problems guidebook filled with practical applications for construction, workshop, and the home.

Download or read book Manga Workshop Characters written by Sophie Chan and published by Penguin. This book was released on 2015-11-01 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create your own manga characters! The manga universe is diverse--full of cute chibis, soulful romantics, cunning villains and sassy schoolgirls. Whether you want to tell love stories, create fantasy worlds or explore the drama of everyday life, you can do it with the help of self-taught manga artist and YouTube celebrity Sophie-Chan. You'll learn to draw personality-filled characters and create unique manga stories from start to finish, even if you've never drawn manga before! Inside Manga Workshop: • 30+ start-to-finish demonstrations teach you to draw women, men and children of all ages, perspectives and personality types, including classic manga schoolgirls, the boy next door, businesswomen, rock stars and gothic vampires. • The Face. Using simple shapes, draw different eyes, noses and mouths to create endless expressions, from blushing surprise and happiness to full-blown tears--even cool hairstyles! • The Figure. Follow easy guidelines to create proportionate characters--chibis and children, high schoolers and warriors--and place them in scenes. Plus, learn the secrets to drawing accurate hands and feet, including shoes! • Color. Learn to color your manga with colored pencil, markers and digital drawing programs to reflect setting, genre, time of day and personality traits. • Bonus pages show variations on facial expressions, common poses, extra outfits and how to use each in your story, plus special drawing demos, including an angel, vampire, witch, a magical cat and Chan's own characters. Includes publishing tips, words of advice and insider secrets!

Download or read book James Christensen written by James Christensen and published by Artisan Books. This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inspired by the world's myths, fables, and tales of imagination, Christensen's paintings reflect the wonder he feels in the world of creativity. 36 paintings.

Download or read book Art Workshop for Children written by Barbara Rucci and published by Quarry Books. This book was released on 2016-11-01 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Art Workshop for Children is not just another book of straightforward art projects. The book's unique child-led approach provides a framework for cultivating creative thinking and encourages the wonder that comes when children are allowed to freely explore the creative process and their materials. As children work through these open-ended workshops, adults are guided on how to be facilitators who provide questions, encourage deep thinking, and help spark an excitement for discovery. Children explore basic materials and workshops that use minimal supplies, and then gradually add new materials to fill the art cabinets as well as new skills and more complex workshops. Most workshops are suitable to preschool-aged children, and each contains ideas for explorations and new twists to engage older or more experienced artists. Interspersed throughout are sidebar essays that introduce perspectives on mess-making, imperfection, the role of adult, collaborative art, and thoughts on the Reggio Emilia method, a self-guided teaching philosophy. These pieces underscore the value of art-making with children, and support the parent/teacher/care-giver on how to successfully lead, question, and navigate their children through the workshops to result in the fullest experiences.

Download or read book Assessing 21st Century Skills written by National Research Council and published by National Academies Press. This book was released on 2011-10-16 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: The routine jobs of yesterday are being replaced by technology and/or shipped off-shore. In their place, job categories that require knowledge management, abstract reasoning, and personal services seem to be growing. The modern workplace requires workers to have broad cognitive and affective skills. Often referred to as "21st century skills," these skills include being able to solve complex problems, to think critically about tasks, to effectively communicate with people from a variety of different cultures and using a variety of different techniques, to work in collaboration with others, to adapt to rapidly changing environments and conditions for performing tasks, to effectively manage one's work, and to acquire new skills and information on one's own. The National Research Council (NRC) has convened two prior workshops on the topic of 21st century skills. The first, held in 2007, was designed to examine research on the skills required for the 21st century workplace and the extent to which they are meaningfully different from earlier eras and require corresponding changes in educational experiences. The second workshop, held in 2009, was designed to explore demand for these types of skills, consider intersections between science education reform goals and 21st century skills, examine models of high-quality science instruction that may develop the skills, and consider science teacher readiness for 21st century skills. The third workshop was intended to delve more deeply into the topic of assessment. The goal for this workshop was to capitalize on the prior efforts and explore strategies for assessing the five skills identified earlier. The Committee on the Assessment of 21st Century Skills was asked to organize a workshop that reviewed the assessments and related research for each of the five skills identified at the previous workshops, with special attention to recent developments in technology-enabled assessment of critical thinking and problem-solving skills. In designing the workshop, the committee collapsed the five skills into three broad clusters as shown below: Cognitive skills: nonroutine problem solving, critical thinking, systems thinking Interpersonal skills: complex communication, social skills, team-work, cultural sensitivity, dealing with diversity Intrapersonal skills: self-management, time management, self-development, self-regulation, adaptability, executive functioning Assessing 21st Century Skills provides an integrated summary of the presentations and discussions from both parts of the third workshop.

Download or read book The Workshop written by and published by . This book was released on 1868 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Science and Deep Learning Workshop For Scientists and Engineers written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2021-11-04 with total page 1977 pages. Available in PDF, EPUB and Kindle. Book excerpt: WORKSHOP 1: In this workshop, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to implement deep learning on recognizing traffic signs using GTSRB dataset, detecting brain tumor using Brain Image MRI dataset, classifying gender, and recognizing facial expression using FER2013 dataset In Chapter 1, you will learn to create GUI applications to display line graph using PyQt. You will also learn how to display image and its histogram. In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, Pandas, NumPy and other libraries to perform prediction on handwritten digits using MNIST dataset with PyQt. You will build a GUI application for this purpose. In Chapter 3, you will learn how to perform recognizing traffic signs using GTSRB dataset from Kaggle. There are several different types of traffic signs like speed limits, no entry, traffic signals, turn left or right, children crossing, no passing of heavy vehicles, etc. Traffic signs classification is the process of identifying which class a traffic sign belongs to. In this Python project, you will build a deep neural network model that can classify traffic signs in image into different categories. With this model, you will be able to read and understand traffic signs which are a very important task for all autonomous vehicles. You will build a GUI application for this purpose. In Chapter 4, you will learn how to perform detecting brain tumor using Brain Image MRI dataset provided by Kaggle (https://www.kaggle.com/navoneel/brain-mri-images-for-brain-tumor-detection) using CNN model. You will build a GUI application for this purpose. In Chapter 5, you will learn how to perform classifying gender using dataset provided by Kaggle (https://www.kaggle.com/cashutosh/gender-classification-dataset) using MobileNetV2 and CNN models. You will build a GUI application for this purpose. In Chapter 6, you will learn how to perform recognizing facial expression using FER2013 dataset provided by Kaggle (https://www.kaggle.com/nicolejyt/facialexpressionrecognition) using CNN model. You will also build a GUI application for this purpose. WORKSHOP 2: In this workshop, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to implement deep learning on classifying fruits, classifying cats/dogs, detecting furnitures, and classifying fashion. In Chapter 1, you will learn to create GUI applications to display line graph using PyQt. You will also learn how to display image and its histogram. Then, you will learn how to use OpenCV, NumPy, and other libraries to perform feature extraction with Python GUI (PyQt). The feature detection techniques used in this chapter are Harris Corner Detection, Shi-Tomasi Corner Detector, and Scale-Invariant Feature Transform (SIFT). In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying fruits using Fruits 360 dataset provided by Kaggle (https://www.kaggle.com/moltean/fruits/code) using Transfer Learning and CNN models. You will build a GUI application for this purpose. In Chapter 3, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying cats/dogs using dataset provided by Kaggle (https://www.kaggle.com/chetankv/dogs-cats-images) using Using CNN with Data Generator. You will build a GUI application for this purpose. In Chapter 4, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting furnitures using Furniture Detector dataset provided by Kaggle (https://www.kaggle.com/akkithetechie/furniture-detector) using VGG16 model. You will build a GUI application for this purpose. In Chapter 5, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying fashion using Fashion MNIST dataset provided by Kaggle (https://www.kaggle.com/zalando-research/fashionmnist/code) using CNN model. You will build a GUI application for this purpose. WORKSHOP 3: In this workshop, you will implement deep learning on detecting vehicle license plates, recognizing sign language, and detecting surface crack using TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries. In Chapter 1, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting vehicle license plates using Car License Plate Detection dataset provided by Kaggle (https://www.kaggle.com/andrewmvd/car-plate-detection/download). In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform sign language recognition using Sign Language Digits Dataset provided by Kaggle (https://www.kaggle.com/ardamavi/sign-language-digits-dataset/download). In Chapter 3, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting surface crack using Surface Crack Detection provided by Kaggle (https://www.kaggle.com/arunrk7/surface-crack-detection/download). WORKSHOP 4: In this workshop, implement deep learning-based image classification on detecting face mask, classifying weather, and recognizing flower using TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries. In Chapter 1, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting face mask using Face Mask Detection Dataset provided by Kaggle (https://www.kaggle.com/omkargurav/face-mask-dataset/download). In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform how to classify weather using Multi-class Weather Dataset provided by Kaggle (https://www.kaggle.com/pratik2901/multiclass-weather-dataset/download). WORKSHOP 5: In this workshop, implement deep learning-based image classification on classifying monkey species, recognizing rock, paper, and scissor, and classify airplane, car, and ship using TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries. In Chapter 1, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform how to classify monkey species using 10 Monkey Species dataset provided by Kaggle (https://www.kaggle.com/slothkong/10-monkey-species/download). In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform how to recognize rock, paper, and scissor using 10 Monkey Species dataset provided by Kaggle (https://www.kaggle.com/sanikamal/rock-paper-scissors-dataset/download). WORKSHOP 6: In this worksshop, you will implement two data science projects using Scikit-Learn, Scipy, and other libraries with Python GUI. In Chapter 1, you will learn how to use Scikit-Learn, Scipy, and other libraries to perform how to predict traffic (number of vehicles) in four different junctions using Traffic Prediction Dataset provided by Kaggle (https://www.kaggle.com/fedesoriano/traffic-prediction-dataset/download). This dataset contains 48.1k (48120) observations of the number of vehicles each hour in four different junctions: 1) DateTime; 2) Juction; 3) Vehicles; and 4) ID. In Chapter 2, you will learn how to use Scikit-Learn, NumPy, Pandas, and other libraries to perform how to analyze and predict heart attack using Heart Attack Analysis & Prediction Dataset provided by Kaggle (https://www.kaggle.com/rashikrahmanpritom/heart-attack-analysis-prediction-dataset/download). WORKSHOP 7: In this workshop, you will implement two data science projects using Scikit-Learn, Scipy, and other libraries with Python GUI. In Project 1, you will learn how to use Scikit-Learn, NumPy, Pandas, Seaborn, and other libraries to perform how to predict early stage diabetes using Early Stage Diabetes Risk Prediction Dataset provided by Kaggle (https://www.kaggle.com/ishandutta/early-stage-diabetes-risk-prediction-dataset/download). This dataset contains the sign and symptpom data of newly diabetic or would be diabetic patient. This has been collected using direct questionnaires from the patients of Sylhet Diabetes Hospital in Sylhet, Bangladesh and approved by a doctor. You will develop a GUI using PyQt5 to plot distribution of features, feature importance, cross validation score, and prediced values versus true values. The machine learning models used in this project are Adaboost, Random Forest, Gradient Boosting, Logistic Regression, and Support Vector Machine. In Project 2, you will learn how to use Scikit-Learn, NumPy, Pandas, and other libraries to perform how to analyze and predict breast cancer using Breast Cancer Prediction Dataset provided by Kaggle (https://www.kaggle.com/merishnasuwal/breast-cancer-prediction-dataset/download). Worldwide, breast cancer is the most common type of cancer in women and the second highest in terms of mortality rates.Diagnosis of breast cancer is performed when an abnormal lump is found (from self-examination or x-ray) or a tiny speck of calcium is seen (on an x-ray). After a suspicious lump is found, the doctor will conduct a diagnosis to determine whether it is cancerous and, if so, whether it has spread to other parts of the body. This breast cancer dataset was obtained from the University of Wisconsin Hospitals, Madison from Dr. William H. Wolberg. You will develop a GUI using PyQt5 to plot distribution of features, pairwise relationship, test scores, prediced values versus true values, confusion matrix, and decision boundary. The machine learning models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, and Support Vector Machine. WORKSHOP 8: In this workshop, you will learn how to use Scikit-Learn, TensorFlow, Keras, NumPy, Pandas, Seaborn, and other libraries to implement brain tumor classification and detection with machine learning using Brain Tumor dataset provided by Kaggle. This dataset contains five first order features: Mean (the contribution of individual pixel intensity for the entire image), Variance (used to find how each pixel varies from the neighboring pixel 0, Standard Deviation (the deviation of measured Values or the data from its mean), Skewness (measures of symmetry), and Kurtosis (describes the peak of e.g. a frequency distribution). It also contains eight second order features: Contrast, Energy, ASM (Angular second moment), Entropy, Homogeneity, Dissimilarity, Correlation, and Coarseness. The machine learning models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, and Support Vector Machine. The deep learning models used in this project are MobileNet and ResNet50. In this project, you will develop a GUI using PyQt5 to plot boundary decision, ROC, distribution of features, feature importance, cross validation score, and predicted values versus true values, confusion matrix, training loss, and training accuracy. WORKSHOP 9: In this workshop, you will learn how to use Scikit-Learn, Keras, TensorFlow, NumPy, Pandas, Seaborn, and other libraries to perform COVID-19 Epitope Prediction using COVID-19/SARS B-cell Epitope Prediction dataset provided in Kaggle. All of three datasets consists of information of protein and peptide: parent_protein_id : parent protein ID; protein_seq : parent protein sequence; start_position : start position of peptide; end_position : end position of peptide; peptide_seq : peptide sequence; chou_fasman : peptide feature; emini : peptide feature, relative surface accessibility; kolaskar_tongaonkar : peptide feature, antigenicity; parker : peptide feature, hydrophobicity; isoelectric_point : protein feature; aromacity: protein feature; hydrophobicity : protein feature; stability : protein feature; and target : antibody valence (target value). The machine learning models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, Gradient Boosting, XGB classifier, and MLP classifier. Then, you will learn how to use sequential CNN and VGG16 models to detect and predict Covid-19 X-RAY using COVID-19 Xray Dataset (Train & Test Sets) provided in Kaggle. The folder itself consists of two subfolders: test and train. Finally, you will develop a GUI using PyQt5 to plot boundary decision, ROC, distribution of features, feature importance, cross validation score, and predicted values versus true values, confusion matrix, training loss, and training accuracy. WORKSHOP 10: In this workshop, you will learn how to use Scikit-Learn, Keras, TensorFlow, NumPy, Pandas, Seaborn, and other libraries to perform analyzing and predicting stroke using dataset provided in Kaggle. The dataset consists of attribute information: id: unique identifier; gender: "Male", "Female" or "Other"; age: age of the patient; hypertension: 0 if the patient doesn't have hypertension, 1 if the patient has hypertension; heart_disease: 0 if the patient doesn't have any heart diseases, 1 if the patient has a heart disease; ever_married: "No" or "Yes"; work_type: "children", "Govt_jov", "Never_worked", "Private" or "Self-employed"; Residence_type: "Rural" or "Urban"; avg_glucose_level: average glucose level in blood; bmi: body mass index; smoking_status: "formerly smoked", "never smoked", "smokes" or "Unknown"; and stroke: 1 if the patient had a stroke or 0 if not. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, XGB classifier, MLP classifier, and CNN 1D. Finally, you will develop a GUI using PyQt5 to plot boundary decision, ROC, distribution of features, feature importance, cross validation score, and predicted values versus true values, confusion matrix, learning curve, performace of the model, scalability of the model, training loss, and training accuracy. WORKSHOP 11: In this workshop, you will learn how to use Scikit-Learn, Keras, TensorFlow, NumPy, Pandas, Seaborn, and other libraries to perform classifying and predicting Hepatitis C using dataset provided by UCI Machine Learning Repository. All attributes in dataset except Category and Sex are numerical. Attributes 1 to 4 refer to the data of the patient: X (Patient ID/No.), Category (diagnosis) (values: '0=Blood Donor', '0s=suspect Blood Donor', '1=Hepatitis', '2=Fibrosis', '3=Cirrhosis'), Age (in years), Sex (f,m), ALB, ALP, ALT, AST, BIL, CHE, CHOL, CREA, GGT, and PROT. The target attribute for classification is Category (2): blood donors vs. Hepatitis C patients (including its progress ('just' Hepatitis C, Fibrosis, Cirrhosis). The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, XGB classifier, MLP classifier, and ANN 1D. Finally, you will develop a GUI using PyQt5 to plot boundary decision, ROC, distribution of features, feature importance, cross validation score, and predicted values versus true values, confusion matrix, learning curve, performace of the model, scalability of the model, training loss, and training accuracy.