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Programming Machine Learning : From Coding to Deep Learning
You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool.But where to start? It's easy to be intimidated, even as a software developer.The good news is that it doesn't have to be that hard.Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system.Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty.Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning.Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work.Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on.Iterate on your design, and add layers of complexity as you go.Build an image recognition application from scratch with supervised learning.Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning.Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets.Train and refine those networks with backpropagation and batching.Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system.Start from the beginning and code your way to machine learning mastery.What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly.Apart from that, you'll only need your computer, and your code-adept brain.
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Model-Driven Software Systems Development Using the Meta-Artifact Process
The importance of architecture for software systems is widely accepted, but the role of architecture in the overall development process is not so clear.Presenting an architecture-centric process, Model-Driven Software Systems Development Using the Meta-Artifact Process makes the role of architecture clear.At its core, this book is about developing software systems and, more specifically, software code.It describes three major innovations for making software, which are combined with five widely used enabling technologies, to provide a complete, hypothesis-driven software development process known as Meta-Artifact Process (MAP).Having complete requirements is essential for making good software and supports the hypothesis-driven MAP. MAP offers properties, qualities, and capabilities that help stakeholders and developers understand and reason about a domain and target systems of interest.MAP, through the central role of the Meta-Artifact and incorporating the view that a computer program is a hypothesis about the requirements, offers new ways to look at systems and their development, even changing the roles of developers and stakeholders. Recommending agile methods wherever appropriate while supporting the OMG Essence standard and working within an overarching architecture, MAP presents ways to ensure that the requirements are complete and correct.It helps to identify likely points during development to form alternative hypotheses about them. Because MAP requires an underlying software development process, it can provide that clarity to existing processes in which the organization’s developers are already proficient. This book provides concrete examples from two broad but diverse areas—Accounting Information Systems in the commercial area and a military command and control system—to show the wide applicability of MAP in both commercial and defense domains.
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Learning, Training, and Development in Organizations
This scholarly book in SIOP’s Organizational Frontier series looks at research on enhancing knowledge acquisition and its application in organizations.It concentrates on training, design and delivery given the changing nature of work and organizations.Now that work is increasingly complex, there is greater emphasis on expertise and cognitive skills.Advances in technology such as computer simulations and web-based training are necessitating a more active role for the learner in the training process.In the broad context of the organization systems, this book promotes learning and development as a continuous lifelong endeavor.
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Effective Software Development for the Enterprise : Beyond Domain Driven Design, Software Architecture, and Extreme Programming
It’s a jungle out there. Delivering software solutions with predictable costs, time, scope, and quality has become more complicated than ever.Developers need to account for multiple moving targets, including often avoided but always relevant factors such as culture, people, and leadership.To effectively deal with these challenges, it’s necessary to rethink the entire delivery chain of modern software development.This book addresses all these topics, putting everything in perspective, from the potential awkwardness created by cultural differences to connecting code with business outcomes to make delivering quality solutions possible.As a software engineer who strives to be his best and challenge the status quo when building IT systems, author Tengiz Tutisani always wanted a book that would cover all of these elements from a developer’s perspective — so he wrote one.Effective Software Development for the Enterprise builds on advanced disciplines, methodologies, and techniques derived from domain-driven design, software architecture, and extreme programming.Its objective is to aid modern software engineers and solution architects in building and delivering high-quality solutions for an enterprise while meeting ambitious criteria:Meet users' expectationsDeliver solutions on time with no defectsCreate products that can scale-out horizontallySolutions should not require a dedicated production support teamAccelerate development paceDouble ROI per developer, team, and softwareYou will learn how to achieve these objectives in any engineering environment by developing solid strategies based on the industry's well-known, recognized, and proven patterns and principles.After reading this book, you will be ready to effectively deal with any and all challenges posed by today’s hyper-competitive, globally-diverse, fast-moving enterprise environment. Who This Book Is ForProfessional software engineers and solution architects, as well as those aspiring to become one.Additionally, software engineering leaders will benefit from reading it, as it will help them maximize their impact via successful software project deliveries.
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Is learning programming and software development very challenging?
Learning programming and software development can be challenging for some people, as it requires logical thinking, problem-solving skills, and attention to detail. However, with dedication, practice, and the right resources, it is definitely achievable. Breaking down complex concepts into smaller, more manageable parts and seeking help from online tutorials, courses, and communities can make the learning process easier and more enjoyable. Ultimately, the level of challenge will vary depending on the individual's background, experience, and learning style.
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What is the multifactorial development model?
The multifactorial development model is a theoretical framework that suggests that human development is influenced by a complex interplay of multiple factors. These factors can include genetic, biological, psychological, environmental, and sociocultural influences. The model emphasizes the dynamic and interactive nature of development, with each factor influencing and being influenced by the others. This approach recognizes that no single factor can fully explain human development, and instead emphasizes the importance of considering the interaction of multiple factors in understanding the complexities of human growth and change.
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Which programming languages are used in software development?
There are many programming languages used in software development, including popular languages such as Java, Python, C++, JavaScript, and Ruby. Each language has its own strengths and is used for different purposes in software development. For example, Java is commonly used for building enterprise-level applications, while Python is known for its simplicity and versatility. C++ is often used for system software and game development, while JavaScript is essential for web development. Overall, the choice of programming language depends on the specific requirements of the software being developed.
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What is the difference between software development and programming?
Software development is a broader term that encompasses the entire process of creating software, including planning, designing, testing, and maintaining software applications. Programming, on the other hand, refers specifically to the act of writing code to instruct a computer to perform certain tasks. While programming is a key component of software development, software development involves a more comprehensive approach that includes various stages beyond just writing code.
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Modern Python Programming using ChatGPT : 10x your software development skills with Python
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Model Building in Mathematical Programming
The 5th edition of Model Building in Mathematical Programming discusses the general principles of model building in mathematical programming and demonstrates how they can be applied by using several simplified but practical problems from widely different contexts.Suggested formulations and solutions are given together with some computational experience to give the reader a feel for the computational difficulty of solving that particular type of model.Furthermore, this book illustrates the scope and limitations of mathematical programming, and shows how it can be applied to real situations.By emphasizing the importance of the building and interpreting of models rather than the solution process, the author attempts to fill a gap left by the many works which concentrate on the algorithmic side of the subject. In this article, H.P. Williams explains his original motivation and objectives in writing the book, how it has been modified and updated over the years, what is new in this edition and why it has maintained its relevance and popularity over the years: http://www.statisticsviews.com/details/feature/4566481/Model-Building-in-Mathematical-Programming-published-in-fifth-edition.html
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Agile Software Development
Agile Software Development is an introduction to agile software development methods.Agile methods try to diminish complexity, increase transparency, and reach a deployable product in a shorter time frame.Agile methods use an iterative and incremental approach to minimize risks and to avoid maldevelopment.The book gives a short introduction to agile methods and agile software development principles.It serves as a study book and as a reference manual.Based on the official Scrum Guide, the book also covers other topics such as best practices for agile software development and agile testing.It targets practitioners who want to start with agile software development, as well as developers or project managers who already use agile methodologies.The book can be read from the beginning, but each chapter has been written in a way so it can be read individually.
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Model-Based Machine Learning
Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains.A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem.This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications.Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions.Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach.The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solve a problem. Features:Explores the assumptions being made by machine learning systems and the effect these assumptions have when the system is applied to concrete problems. Explains machine learning concepts as they arise in real-world case studies. Shows how to diagnose, understand and address problems with machine learning systems. Full source code available, allowing models and results to be reproduced and explored. Includes optional deep-dive sections with more mathematical details on inference algorithms for the interested reader.
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Which PC at Hi Tech is a good 700 model?
The Hi Tech PC-700X is a good model that offers a balance of performance and affordability. It comes with a powerful processor, ample RAM, and a decent amount of storage, making it suitable for everyday tasks and light gaming. Additionally, it has a sleek design and a variety of connectivity options, making it a good choice for users looking for a reliable and versatile PC.
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What are examples of the psychosocial development model?
Examples of the psychosocial development model include Erik Erikson's stages of psychosocial development, which outline the different challenges individuals face at each stage of life, such as trust vs. mistrust in infancy, autonomy vs. shame and doubt in toddlerhood, and identity vs. role confusion in adolescence. Another example is the attachment theory, which focuses on the importance of early relationships in shaping an individual's social and emotional development. Additionally, the social learning theory, proposed by Albert Bandura, emphasizes the role of observation and imitation in the development of behaviors and attitudes.
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What is Erikson's stages of psychosocial development model?
Erikson's stages of psychosocial development model is a theory that outlines the eight stages of human development from infancy to old age. Each stage represents a specific psychosocial crisis or challenge that individuals must navigate in order to develop a healthy sense of self and relationships with others. These stages include trust vs. mistrust, autonomy vs. shame and doubt, initiative vs. guilt, industry vs. inferiority, identity vs. role confusion, intimacy vs. isolation, generativity vs. stagnation, and integrity vs. despair. Erikson believed that successfully resolving these crises at each stage leads to the development of important virtues and a sense of personal competence.
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What training opportunities are available for IT specialists to specialize in web development and general programming, such as software development?
There are various training opportunities available for IT specialists looking to specialize in web development and general programming. Online platforms like Coursera, Udemy, and Codecademy offer courses and certifications in programming languages such as Python, Java, and JavaScript. Additionally, coding bootcamps like General Assembly and Flatiron School provide intensive, hands-on training in software development. IT specialists can also pursue advanced degrees in computer science or related fields to deepen their knowledge and skills in web development and programming.
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