Accelerating Development Velocity Using DockerDiscover how a software engineer can leverage Docker in order to expedite development velocity. This book focuses on the fundamental concepts this program is built upon and explores how it can help you get your services up and running inside Docker containers. You'll also review tips on how to debug microservices applications that run inside Docker containers.
Tech companies are now developing complex softwares that are comprised of multiple services running on different platforms, and Docker has become an essential part of coordinating the communication between these services and platforms.
This book addresses problems caused by drifting microservices, debugging across services, inconsistent environments across machines, and coordinating development of machine learning systems between a team of developers, etc. Accelerating Development Velocity Using Docker puts you on the path to transforming your complex systems into more efficient ones.
Setup Docker and employ quick solut ...
Exploring Data ScienceThere's never been a better time to get into data science. But where do you start? Data Science is a broad field, incorporating aspects of statistics, machine learning, and data engineering. It's easy to become overwhelmed, or end up learning about a small section of data science or a single methodology.
Exploring Data Science is a collection of five hand-picked chapters introducing you to various areas in data science and explaining which methodologies work best for each. John Mount and Nina Zumel, authors of Practical Data Science with R, selected these chapters to give you the big picture of the many data domains. You'll learn about time series, neural networks, text analytics, and more. As you explore different modeling practices, you'll see practical examples of how R, Python, and other languages are used in data science. Along the way, you'll experience a sample of Manning books you may want to add to your library. ...
Exploring the Data JungleSome people like to believe that all data is ready to be used immediately. Not so! Data in the wild is hard to track and harder to understand, and the first job of data scientists to identify and prepare data so it can be used. To find your way through the data jungle successfully, you need the right perspective and guidance. (There's no point hacking at overgrowth with a spoon after all!) Identify and prepare your data well, and you'll be well set to create insight from chaos and discover important analytic patterns - to set your business on the right track.
Exploring the Data Jungle: Finding, Preparing, and Using Real-World Data is a collection of three hand-picked chapters introducing you to the often-overlooked art of putting unfamiliar data to good use. Brian Godsey, author of Think Like a Data Scientist, has selected these chapters to help you navigate data in the wild, identify and prepare raw data for analysis, modeling, machine learning, or visualization. As you explore the ...
Hands-On Industrial Internet of ThingsWe live in an era where advanced automation is used to achieve accurate results. To set up an automation environment, you need to first configure a network that can be accessed anywhere and by any device. This book is a practical guide that helps you discover the technologies and use cases for Industrial Internet of Things (IIOT).
Hands-On Industrial Internet of Things takes you through the implementation of industrial processes and specialized control devices and protocols. You'll study the process of identifying and connecting to different industrial data sources gathered from different sensors. Furthermore, you'll be able to connect these sensors to cloud network, such as AWS IoT, Azure IoT, Google IoT, and OEM IoT platforms, and extract data from the cloud to your devices.
As you progress through the chapters, you'll gain hands-on experience in using open source Node-Red, Kafka, Cassandra, and Python. You will also learn how to develop streaming and batch-based Machine Learni ...
Hands-On Data Science with SQL Server 2017SQL Server is a relational database management system that enables you to cover end-to-end data science processes using various inbuilt services and features.
Hands-On Data Science with SQL Server 2017 starts with an overview of data science with SQL to understand the core tasks in data science. You will learn intermediate-to-advanced level concepts to perform analytical tasks on data using SQL Server. The book has a unique approach, covering best practices, tasks, and challenges to test your abilities at the end of each chapter. You will explore the ins and outs of performing various key tasks such as data collection, cleaning, manipulation, aggregations, and filtering techniques. As you make your way through the chapters, you will turn raw data into actionable insights by wrangling and extracting data from databases using T-SQL. You will get to grips with preparing and presenting data in a meaningful way, using Power BI to reveal hidden patterns. In the concluding chapters, you wi ...
Hands-On Data Science with RR is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems.
The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data.
Towards the end, you will also learn ...
Python for Data Mining Quick Syntax ReferenceLearn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.
Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You'll be introduced to several data mining packages, with examples of how to use each of them.
The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning.
Install Python and choose a development environment; Understand the basic concepts of object-oriented programming; Imp ...
Practical Apache SparkWork with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You'll follow a learn-to-do-by-yourself approach to learning - learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure.
On completion, you'll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You'll also become familiar with machine learning algorithms with real-time usage.
Discover the functional programming features of Scala; Understand the complete architecture of Spark and its components; Integrate Apache Spark with Hive and Kafka; Use Spark SQL, DataF ...
Hands-On Geospatial Analysis with R and QGISManaging spatial data has always been challenging and it's getting more complex as the size of data increases. Spatial data is actually big data and you need different tools and techniques to work your way around to model and create different workflows. R and QGIS have powerful features that can make this job easier.
This book is your companion for applying machine learning algorithms on GIS and remote sensing data. You'll start by gaining an understanding of the nature of spatial data and installing R and QGIS. Then, you'll learn how to use different R packages to import, export, and visualize data, before doing the same in QGIS. Screenshots are included to ease your understanding.
Moving on, you'll learn about different aspects of managing and analyzing spatial data, before diving into advanced topics. You'll create powerful data visualizations using ggplot2, ggmap, raster, and other packages of R. You'll learn how to use QGIS 3.2.2 to visualize and manage (create, edit, and fo ...
Unity Artificial Intelligence Programming, 4th EditionDeveloping Artificial Intelligence (AI) for game characters in Unity 2018 has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from the basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters.
This fourth edition with Unity will help you break down AI into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts and features related to game AI in Unity.
Further on, you'll learn how to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM).
Next, you'll l ...