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Author : Christopher M. Frenz
Publisher : Apress
Page : 345 pages
File Size : 50,9 Mb
Release : 2002-01-31
Category : Computers
ISBN : 9781430211396
Here is a concise and practical guide to help researchers and engineers who are new to Visual Basic gain a firm grasp of the topics that are most relevant to their programming needs.
Author : Paul Vick
Publisher : Addison-Wesley Professional
Page : 438 pages
File Size : 43,6 Mb
Release : 2004
Category : Computers
ISBN : 0321169514
Praise for The Visual Basic .NET Programming Language "There is no substitute to getting the inside scoop directly from a book written by the father of a programming language such as Bjarne Stroustrup for C++, James Gosling for Java and Alan Cooper for the original version of Visual Basic. Paul Vick, the father of Visual Basic .NET, explains the whys and hows of this exciting new language better than any other human being on the planet." --Ted Pattison, Barracuda.NET "The Visual Basic .NET Programming Language includes nuances that in all my use and study of VB .NET, I haven''t seen discussed anywhere else. For example, I learned that you can use the Imports statement to import an Enum name, so that you needn''t refer to the enum in all its uses. In addition, I learned that the dictionary lookup operator, ''!'', works in VB .NET--I thought this one had been retired. In any case, if you''re searching for a book that covers all the language syntax issues, and more, Paul Vick''s book is a great place to look." --Ken Getz, Senior Consultant, MCW Technologies, LLC "This book is an excellent stepping stone for Visual Basic developers wanting to get their toes wet in the .NET waters. Paul''s presentation of the core topics all VB developers should tackle first is clear, concise, and unlike other books in the genre, does not overwhelm the reader. The VB6 vs. VB.NET task-oriented approach guides you through the new language and OO features, and then moves to basic threading and other CLR topics--as well as to the key points in the COM to .NET transition--in a well thought-out sequence. If you''ve been holding out on VB .NET, this is a great book to get you started." --Klaus H. Probst, Sr. Consultant/Architect, Spherion Technology Services, Microsoft MVP "There is no shortage of VB .NET books in the market, but this is the only book straight from the creators. While that is an excellent reason in itself for reading this book, it is the brevity and clarity of the content, along with the examples, that makes this book a must-have." --Amit Kalani, Developer "Overall, I liked this book and it definitely benefited me. I learned new things I didn''t see anywhere else and I''ll certainly put these to good use in the future. Paul''s book makes a great reference manual for intermediate and advanced VB .NET developers." --Philip Williams, System Engineer, LDC Direct "This book contains a lot of great information I have seen nowhere else and addresses issues that other books do not." --Ethan Roberts, .NET Architect, General Casualty "This book is full of useful information and provides a good historical background for the Visual Basic .NET Language." --Dave Vitter, Technical Lead Developer and author of Designing Visual Basic .NET Applications (Coriolis, 2001) The definitive Microsoft Visual Basic .NET reference--authored by Visual Basic .NET''s lead architect If you want to leverage all of VB .NET''s immense power, get this book. It''s the definitive VB .NET reference and tutorial, and the first Visual Basic book written by one of VB .NET''s lead architects. No other book offers this much behind-the-scenes insight about why VB .NET works the way it does, how it evolved, and how you can make the most of it. The Visual Basic .NET Programming Language is a superb learning tool for new VB .NET programmers and a must-have reference for developers at every level. Paul Vick presents precise language descriptions, essential reference materials, practical insights, and hundreds of code samples, straight from Microsoft''s VB .NET design team. Just some of the features include: A history and overview of Visual Basic''s evolution into VB .NET Complete coverage of the language syntax Transitioning from COM to the CLR and leveraging the .NET platform Runtime functions Taking full advantage of VB .NET''s object-oriented features Notes on style, design, and compatibility throughout the text Notes for the advanced user throughout the text Vick exposes VB .NET''s most powerful capabilities with unprecedented depth and clarity, and packs this book with information you simply won''t find anywhere else. Whether you''re an experienced VB .NET programmer, upgrading from earlier versions of Visual Basic, or coming to Visual Basic and .NET for the first time, you''ll find this book indispensable.
Author : Namir Clement Shammas
Publisher : McGraw-Hill Companies
Page : 251 pages
File Size : 46,6 Mb
Release : 1996-01
Category : Mathematics
ISBN : 0079120032
This valuable book/disk offers scientists, engineers, statisticians and programmers a toolbox of essential numerical routines in Visual Basic. Providing the routines in Visual Basic offers an excellent method for scientists and engineers familiar with BASIC to learn Visual Basic through mathematical routines they can use every day in their work.
Author : Mark F. Russo,Martin M. Echols
Publisher : John Wiley & Sons
Page : 390 pages
File Size : 49,6 Mb
Release : 1999-03-31
Category : Computers
ISBN : 9780471254935
Laboranten und Analytiker stehen häufig vor einem gravierenden Problem: Einerseits benötigen sie Steuerprogramme für Instrumente und einfache Software zur Sammlung, Speicherung und rudimentären Auswertung ihrer Daten - andererseits haben sie in der Regel keine Programmiererfahrung. Dieser Band erklärt die Visual-Basic-Entwicklungsumgebung so unkompliziert und praxisnah, daß jeder Wissenschaftler und Ingenieur in die Lage versetzt wird, grundlegende, für sein Problem maßgeschneiderte Anwendungen selbst zu erstellen. (05/99)
Author : Arun Datta
Publisher : CRC Press
Page : 642 pages
File Size : 41,9 Mb
Release : 2013-09-20
Category : Science
ISBN : 9781439862803
Software tools are a great aid to process engineers, but too much dependence on such tools can often lead to inappropriate and suboptimal designs. Reliance on software is also a hindrance without a firm understanding of the principles underlying its operation, since users are still responsible for devising the design. In Process Engineering and Design Using Visual Basic, Arun K. Datta provides a unique and versatile suite of programs along with simultaneous development of the underlying concepts, principles, and mathematics. Each chapter details the theory and techniques that provide the basis for design and engineering software and then showcases the development and utility of programs developed using the material outlined in the chapter. This all-inclusive guide works systematically from basic mathematics to fluid mechanics, separators, overpressure protection, and glycol dehydration, providing basic design guidelines based on international codes. Worked examples demonstrate the utility of each program, while the author also explains problems and limitations associated with the simulations. After reading this book you will be able to immediately put these programs into action and have total confidence in the result, regardless of your level of experience. Companion Visual Basic and Excel files are available for download on under the "Downloads/Updates" tab on this web page.
Author : Richard Schlesinger
Publisher : Jones & Bartlett Learning
Page : 37 pages
File Size : 46,8 Mb
Release : 2007-03
Category : Computers
ISBN : 9780763750602
An excellent supplement to Computer Science Illuminated, Third Edition, as well as an informative primer, Visual Basic .NET: The Programming Language, provides a straightforward introduction to this user-friendly language. This overview describes the fundamentals of the object-oriented VB .NET environment, the structure of VB .NET programs, and much more. Novice programmers will be relieved that this functional programming language is easy to learn and compatible with many other languages using the new .NET framework.This title is only available when bundled with a text. Contact your Publisher's Representative for more information.
Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 1977 pages
File Size : 50,6 Mb
Release : 2021-11-04
Category : Computers
ISBN : 8210379456XXX
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.
Author : Jesse Liberty
Publisher : "O'Reilly Media, Inc."
Page : 564 pages
File Size : 47,5 Mb
Release : 2003
Category : Computers
ISBN : 0596004389
Completely revised, this edition is an essential guide for VB programmers looking to make the change to the .NET programming environment.
Author : ANONIMO,Harvey M. Deitel,Paul J. Deitel,Tem R. Nieto
Publisher : Prentice Hall
Page : 1572 pages
File Size : 51,9 Mb
Release : 2002-07-01
Category : Electronic
ISBN : 0130425419
Appropriate for beginning to intermediate courses on Visual Basic and Visual Basic .NET programming offered in departments of Computer Science, CIS, MIS, IT, Business, Engineering and Continuing Education. The ultimate Visual Basic .NET programming package. The Complete Visual Basic .NET Training Course, Student Edition features the Deitel Visual Basic .NET How to Program text along with a fully-interactive CD-ROMThe Visual Basic .NET Multimedia Cyber Classroomand provides students and programmers with the ideal medium for learning how to program with Visual Basic .NET. It's a proven fact that the more involved students are, the more they learn. That's what The Complete Visual Basic .NET Training Course is all abouthelping students learn in every way possible.
Author : Shirish Chavan
Publisher : Pearson Education India
Page : 592 pages
File Size : 44,8 Mb
Release : 2004-09
Category : BASIC (Computer program language)
ISBN : 8131713911
Visual Basic.NET has been written keeping in mind courses in Visual Programming offered in B.E., B.Tech, BSc (Computer Science), IT BCA, MCA, and professional courses. The book is ideally designed for the beginner to the intermediate level readers.
Author : Ying Bai
Publisher : John Wiley & Sons
Page : 898 pages
File Size : 47,9 Mb
Release : 2012-05-09
Category : Computers
ISBN : 9781118249826
Practical Database Programming with Visual Basic.NET The most up-to-date Visual Basic.NET programming textbook—covering both fundamentals and advanced-level programming techniques—complete with examples and solutions Visual Basic.NET (VB.NET) is an object-oriented computer programming language that can be viewed as an evolution of the classic Visual Basic (VB), which is implemented on the .NET Framework. Microsoft currently supplies two major implementations of Visual Basic: Microsoft Visual Studio (which is commercial software) and Microsoft Visual Studio Express (which is free of charge). Forgoing the large amounts of programming codes found in most database programming books, Practical Database Programming with Visual Basic.NET shows students and professionals both how to develop professional and practical database programs in a Visual Basic.NET environment by using Visual Studio.NET Data Tools and Wizards related to ADO.NET 4.0, and how to apply codes that are auto-generated by solely using Wizards. The fully updated Second Edition: Covers both fundamentals and advanced database programming techniques Introduces three popular database systems with practical examples including MS Access, SQL Server 2008, and Oracle Features more than fifty sample projects with detailed illustrations and explanations to help students understand key techniques and programming technologies Includes downloadable programming codes and exercise questions This book provides undergraduate and graduate students as well as database programmers and software engineers with the necessary tools to handle the database programming issues in the Visual Studio.NET environment.
Author : Jonathan Morrison,Gary Cornell
Publisher : Apress
Page : 518 pages
File Size : 51,9 Mb
Release : 2008-01-01
Category : Computers
ISBN : 9781430208471
In Programming VB .NET: A Guide for Experienced Programmers, authors Gary Cornell and Jonathan Morrison carefully explain the exciting features of Visual Basic .NET. Since VB .NET is, for all practical purposes, a whole new language even for the most experienced Visual Basic programmers, developers need to think differently about many familiar topics. Cornell and Morrison are there to help you with careful discussions of each topic. Cornell and Morrison write from the point of view of the experienced programmer, with constant references to the changes from earlier versions of VB. Developers learn how to use VB .NET for database programming through ADO.NET and web programming through ASP.NET. After reading Programming VB .NET: A Guide for Experienced Programmers, developers will have a firm grasp of the exciting VB .NET language and its uses in creating powerful .NET applications.
Author : Richard Blair,Jonathan Crossland,Matthew Reynolds,Thearon Willis
Publisher : John Wiley & Sons
Page : 880 pages
File Size : 54,8 Mb
Release : 2004-08-18
Category : Computers
ISBN : 9780764558696
What is this book about? Visual Basic .NET is the latest version of the most widely used programming language in the world, popular with professional developers and complete beginners alike. This book will teach you Visual Basic .NET from first principles. You'll quickly and easily learn how to write Visual Basic .NET code and create attractive windows and forms for the users of your applications. To get you started on the road to professional development, you'll also learn about object-oriented programming, creating your own controls, working with databases, creating menus, and working with graphics. This second edition has been thoroughly tested on the full release version of .NET. The book is written in the proven Wrox beginning style with clear explanations and plenty of code samples. Every new concept is explained thoroughly with Try It Out examples and there are end-of-chapter questions to test yourself. What does this book cover? In this book, you will learn how to Install Visual Basic .NET Write Visual Basic .NET code Understand what the .NET Framework is and why it's important Control the flow through your application with loops and branching structures Create useful windows and screens Create your own menus Gain a complete understanding of object-oriented programming Work with graphics Create your own controls Access databases with ADO.NET Create applications for the Web Who is this book for? This book is aimed at readers who wish to learn to program using Visual Basic .NET. It assumes you have no prior experience of programming, but moves at a fast enough pace to be interesting if you have programmed in another language.
Author : Vincent Himpe
Publisher : Elektor International Media
Page : 474 pages
File Size : 52,8 Mb
Release : 2006
Category : Computers
ISBN : 0905705688
Intended for those people who want to control existing or self-built hardware from their computer. This book shows you advanced things like: using tools like Debug to find hardware addresses, setting up remote communication using TCP/IP and UDP sockets and even writing your own internet servers.
Author : Anonim
Publisher : Unknown
Page : 532 pages
File Size : 42,8 Mb
Release : 2003
Category : Chemistry, Technical
ISBN : STANFORD:36105113168731