Go Machine Learning Projects
Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured.
The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate m ...
Scaling Your Node.js Apps
Take your Node.js application into production-ready status, capable of scaling up to whatever your needs might be. You'll discover that architecting for successful, popular sites is an essential tool of any professional Node.js developer, and learning to scale your own applications is a great place to start.
Using this book you will learn when to scale, what factors should trigger scaling, and what architectural techniques are best suited for scaling. You will also explore common pitfalls that arise when scaling a Node.js application and solutions to correct them.
Including analyses of success cases at the largest-scale companies, such as Netflix and Paypal, this book will get you started with scaling in no time at all.
Determine what factors should trigger the need to scale; Discover different architectural patterns that lend themselves to scaling; Resolve problems that arise when scaling up a Node.js application; Monitor a platform in order to understand when to start scali ...
Practical React Native
Discover how to use React Native in the real world, from scratch. This book shows you what React Native has to offer, where it came from, and where it's going.
You'll begin with a solid foundation of practical knowledge, and then build on it immediately by constructing three different apps. You'll learn how to use each feature of React Native by working on two full projects and one full game. These aren't just simple React Native Hello World examples (although you'll naturally start there!) but are apps that you can, if you so choose, install on your mobile devices and use for real.
Throughout this book, you'll gain real-world familiarity with React Native as well as supporting components from Expo, NativeBase, React Navigation and the Redux and Lodash libraries. You'll also build server-side code for a mobile React Native app to talk to using the popular Node.js and Socket.io library, providing you a holistic view of things even beyond React Native. And, you'll see many helpfu ...
Agile Office 365
Plan, deploy, and run Office 365 using an agile project management approach. This soup-to-nuts guide teaches you how to apply agile techniques in order to make your Office 365 implementation a success, even as the Microsoft Office 365 platform continues to evolve and introduce new features.
The author's approach to teaching time- and resource-saving concepts mirrors the process a team might typically encounter in delivering software projects. Learning begins with an overview of Office 365 and Agile. From there, you delve into topics correlating to product conception, execution, and deployment. The book wraps up with a comprehensive discussion on how Office 365, straight out of the box, can be used as a tool to manage Office 365 deployments and other types of projects.
Understand what Office 365 is and why it is the world's most popular online business app; Adapt your delivery process to work with Office 365 and its regular update schedule; Recognize potential risk areas an ...
Machine Learning with AWS
Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models.
By the end of this book, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects. ...
Internet of Things Programming Projects
The Internet of Things (IOT) has managed to attract the attention of researchers and tech enthusiasts, since it powerfully combines classical networks with instruments and devices.
In Internet of Things Programming Projects, we unleash the power of Raspberry Pi and Python to create engaging projects. In the first part of the book, you'll be introduced to the Raspberry Pi, learn how to set it up, and then jump right into Python programming. Then, you'll dive into real-world computing by creating a "Hello World" app using flash LEDs.
As you make your way through the chapters, you'll go back to an age when analog needle meters ruled the world of data display. You'll learn to retrieve weather data from a web service and display it on an analog needle meter, and build a home security system using the Raspberry Pi. The next project has a modern twist, where we employ the Raspberry Pi to send a signal to a web service that will send you a text when someone is at the door. In the ...
Machine Learning Projects for Mobile Applications
Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so.
The book starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks. You will start by developing an app to classify age and gender using Core ML and Tensorflow Lite. You will explore neural style transfer and get familiar with how deep CNNs work. We will also take a closer look at Google's ML Kit for the Firebase SDK for mobile applications. You will learn how to detect handwritten text on mobile. You will also learn how to create your own Snapchat filter by making use of facial attributes and OpenCV. You will learn how to train your own food classification model on your mobile; all of this will be done with the help of deep learning techniques. Lastly, you will build an image classifier on your mobile, com ...
Python Deep Learning Projects
Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.
Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.
Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects.
By the end of ...
After a brief history of Python and key differences between Python 2 and Python 3, you'll understand how Python has been used in applications such as YouTube and Google App Engine. As you work with the language, you'll learn about control statements, delve into controlling program flow and gradually work on more structured programs via functions.
As you settle into the Python ecosystem, you'll learn about data structures and study ways to correctly store and represent information. By working through specific examples, you'll learn how Python implements object-oriented programming (OOP) concepts of abstraction, encapsulation of data, inheritance, and polymorphism. You'll be given an overview of how imports, modules, and packages work in Python, how you can handle errors to prevent apps from crashing, as well as file manipulation.
By the end of this book, you'll have built up an impressive portfolio of projects and armed yourself with the skills you need to tackle Python projects i ...
Practical Java Machine Learning
Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.
Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualization for Java; document classification using ...
Impractical Python Projects
Impractical Python Projects picks up where the complete beginner books leave off, expanding on existing concepts and introducing new tools that you'll use every day. And to keep things interesting, each project includes a zany twist featuring historical incidents, pop culture references, and literary allusions.
You'll flex your problem-solving skills and employ Python's many useful libraries to do things like: Help James Bond crack a high-tech safe with a hill-climbing algorithm; Write haiku poems using Markov Chain Analysis; Use genetic algorithms to breed a race of gigantic rats; Crack the world's most successful military cipher using cryptanalysis; Foil corporate security with invisible electronic ink; Derive the anagram, "I am Lord Voldemort" using linguistical sieves; Plan your parents secure retirement with Monte Carlo simulation; Save the sorceress Zatanna from a stabby death using palingrams; Model the Milky Way and calculate our odds of detecting alien civilizations; ...