Видавець: 16
Rui Miguel Forte
This book is intended for the budding data scientist, predictive modeler, or quantitative analyst with only a basic exposure to R and statistics. It is also designed to be a reference for experienced professionals wanting to brush up on the details of a particular type of predictive model. Mastering Predictive Analytics with R assumes familiarity with only the fundamentals of R, such as the main data types, simple functions, and how to move data around. No prior experience with machine learning or predictive modeling is assumed, however you should have a basic understanding of statistics and calculus at a high school level.
James D. Miller , Rui Miguel Forte
R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks.By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R.
Alvaro Fuentes
Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics.By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysis.
Russell Anderson-Williams
Prezi is a tool for delivering presentations in a linear or non-linear format. This cloud-based software enables users to structure presentations on an infinite canvass in a way that is much more engaging and visually stimulating to the audience.Mastering Prezi for Business Presentations is a must read for anyone already using Prezi who wants to take their presentations to the next level. It covers all of the technical elements of the software, whilst also looking at the practicalities of using Prezi in a business environment.This book covers all the technical elements of Prezi and also teaches the reader how to think for Prezi, and approach their design in the best way. This is an essential resource for people who want to use Prezi seriously.As well as covering best practices for inserting imagery, sound, and video, this book also covers topics for business users like collaborating and sharing Prezis online, using Prezi at a meeting to brain storm with overseas colleagues, and how to 'Prezify' PowerPoint or Keynote slides.Mastering Prezi for Business Presentations will escalate you from Prezi user to master with ease.
Russell Anderson-Williams, John J Sylvia IV
If you use Prezi in business and want to take your presentations to the next level, or if you want to become the office Prezi master, this book is for you.
Ankur Ankan
Probabilistic Graphical Models is a technique in machine learning that uses the concepts of graph theory to compactly represent and optimally predict values in our data problems. In real world problems, it's often difficult to select the appropriate graphical model as well as the appropriate inference algorithm, which can make a huge difference in computation time and accuracy. Thus, it is crucial to know the working details of these algorithms.This book starts with the basics of probability theory and graph theory, then goes on to discuss various models and inference algorithms. All the different types of models are discussed along with code examples to create and modify them, and also to run different inference algorithms on them. There is a complete chapter devoted to the most widely used networks Naive Bayes Model and Hidden Markov Models (HMMs). These models have been thoroughly discussed using real-world examples.
Edward Unger, Ryan Coyne
Do you want to start a business or turn a hobby into a profession, but feel like you're running out of time? Do you want to become a productivity powerhouse, effectively juggling personal and professional responsibilities? Does your team need help boosting efficiency? This comprehensive guide provides practical strategies and action plans to optimize your work and home life using ClickUp.Achieve project success by setting meaningful KPIs, creating team dashboards, generating real-time reports, and extending ClickUp with integrations. You’ll learn how to implement and optimize your workspace structure, project management, processes, workflows, automation, AI, and how to use ClickUp Brain as a knowledgebase. This book also helps you master ClickUp for home life by using it to manage personal tasks, plan vacations, collaborate on projects, maintain interactive inventory, and track household chores. Finally, you'll explore advanced features, goal setting, and personal approaches to maximize your leverage of ClickUp as your 'accomplishment system.Whether you're a seasoned user or just getting started, this ClickUp handbook provides best practices and highlights common mistakes for implementing and optimizing ClickUp to unlock its potential and achieve your goals.
William Hegedus
With growing focus on observability and reliability, establishing a scalable and reliable monitoring environment is more important than ever. Over the last decade, Prometheus has emerged as the leading open-source, time-series based monitoring software catering to this demand. Written by an open-source advocate and Prometheus contributor, this guide provides an in-depth look at Prometheus, covering best practices and offering insights into scaling, operating, and extending Prometheus, from small on-premises workloads to multi-cloud, globally distributed environments.The book helps you revisit the basics of Prometheus, before moving on to advanced techniques of observability and monitoring using Prometheus. You’ll find out how to deploy Prometheus on Kubernetes and achieve an HA alerting infrastructure in Prometheus. You’ll also learn to leverage Prometheus in your daily operations through alerts, Grafana dashboards, and building your own exporter. Finally, you’ll explore various open-source projects that extend the functionality of Prometheus, help with various aspects of running Prometheus at scale, and make the most of Prometheus data.By the end of this book, you’ll be able to confidently build, automate, and deliver your infrastructure and CI/CD pipelines in cloud-based applications.