Robert Thas John – författare

Gain expert guidance on how to successfully develop machine learning models in Python and build your own unique data platformsKey FeaturesGain a full understanding of the model production and deployment processBuild your first machine learning model in just five minutes and get a hands-on machine learning experienceUnderstand how to deal with common challenges in data science projectsBook DescriptionWhere there’s data, there’s insight. With so much data being generated, there is immense scope to extract meaningful information that’ll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you’ll open new career paths and opportunities.The Data Science Workshop begins by introducing different types of projects and showing you how to incorporate machine learning algorithms in them. You’ll learn to select a relevant metric and even assess the performance of your model. To tune the hyperparameters of an algorithm and improve its accuracy, you’ll get hands-on with approaches such as grid search and random search.Next, you’ll learn dimensionality reduction techniques to easily handle many variables at once, before exploring how to use model ensembling techniques and create new features to enhance model performance. In a bid to help you automatically create new features that improve your model, the book demonstrates how to use the automated feature engineering tool. You’ll also understand how to use the orchestration and scheduling workflow to deploy machine learning models in batch.By the end of this book, you’ll have the skills to start working on data science projects confidently. By the end of this book, you’ll have the skills to start working on data science projects confidently.What you will learnExplore the key differences between supervised learning and unsupervised learningManipulate and analyze data using scikit-learn and pandas librariesUnderstand key concepts such as regression, classification, and clusteringDiscover advanced techniques to improve the accuracy of your modelUnderstand how to speed up the process of adding new featuresSimplify your machine learning workflow for productionWho this book is forThis is one of the most useful data science books for aspiring data analysts, data scientists, database engineers, and business analysts. It is aimed at those who want to kick-start their careers in data science by quickly learning data science techniques without going through all the mathematics behind machine learning algorithms. Basic knowledge of the Python programming language will help you easily grasp the concepts explained in this book.

Build real-world, scalable, and fault-tolerant IoT systems using Arduino MKR boards that collect, transmit, and store data on a massive scale in a structured databaseKey FeaturesSet up databases to store and retrieve information collected from various sensorsIngest your data into your database for storage with REST APIs and MQTTCommunicate with your application layer using different communication technologies from Arduino MKR and Portenta H7Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionIn our modern, internet-connected world, where billions of devices constantly collect and send data to systems to be stored and processed, it’s surprising how the intricacies of data transmission and storage are often overlooked in the IoT domain. With Arduino Data Communications, you'll bridge the knowledge gap and become an expert in collecting data from IoT sensors, transmitting data, and configuring your own databases.This book is an exploration of IoT’s inner workings, guiding you through the process of setting up an end-to-end system that you can employ to prototype your own IoT solutions, using easy-to-follow examples. It begins with a general overview of the Arduino ecosystem, acquainting you with various sensors and shields and unveiling the art of data collection. You’ll then explore data formats and methods to store data, both locally and on database servers. As you progress through the chapters, you’ll learn how to set up REST and MQTT infrastructure to communicate with databases and get hands-on with LoRaWAN, Ethernet, cellular, HC-12, and RS-485. The final chapters are your training ground for real-world projects, imparting the essential knowledge you need to tackle complex challenges with confidence.By the end of this Arduino book, you'll have seamlessly configured an end-to-end system, all while immersing yourself in practical scenarios that bring the world of IoT to life.What you will learnExplore data storage formats for both local and remote storage solutionsBuild projects that leverage the variety of communication standardsSet up a database to host data transmitted from various projectsUse MQTT and RESTful APIs to send data from devices to remote systemsPrepare for multiple devices using high availability measuresUse LoRa by implementing a gateway and a clientTransmit temperature and humidity data over RS-485 and HC-12Who this book is forThis book is for embedded systems engineers and electronics engineers who want to build IoT devices and gain insights into storing data collected from these devices, as well as establish communication between devices. The skills you learn in this book will come in handy even if your final product isn't built on Arduino. While prior experience with computers is assumed, expertise with embedded systems such as Arduino is not a prerequisite. Familiarity with Arduino programming will be beneficial, but not necessary.