Biznes IT
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, 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.
Samir Madhavan
Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving.This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science.Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods.Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics.
James Ma Weiming
If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.
ANDRIY LESYUK
Redmine is not only one of the popular open source project management applications but also one of the best project hosting and issue tracking solutions.This book is an update of our previous successful edition, Mastering Redmine. This book is a comprehensive guide that will give you a detailed practical understanding on how to effectively manage, monitor and administer complex projects using Redmine.You will get familiar with the concept of Issue Tracking and will get to know why and what makes Redmine one of the best issue trackers. Another main part of Redmine functionality, which is Managing projects shows why this is one of the best applications for project hosting. Furthermore, you will learn more about Redmine rich text formatting syntax, access control and workflow and time Tracking. Towards the end, you will unleash the power of custom fields and guides to show how to customize Redmine without breaking upgrade compatibility.By the end of the book, you will have a deep practical understanding on how to effectively monitor and manage large scale and complex projects using Redmine.
Mastering Salesforce Experience Cloud. Strategies for creating powerful customer interactions
Lillie Beiting, Rachel Rogers
Empowering your target audience to interact effortlessly with you and your product offerings is a critical aspect of business in the modern era. Users expect easy, professional digital experiences when engaging with organizations. However, creating engagement applications from scratch is challenging, and connecting user behavior with your organization’s data is even more complex. Enter Salesforce Experience Cloud sites, website portals built on the Salesforce data model that seamlessly connects your user data to your user experience. Mastering Salesforce Experience Cloud focuses on the human-centric nature of this product, beginning with a comprehensive guide on designing for your organization’s desired users and ensuring success for both internal teams and end users. After exploring the real-world applications of Experience Cloud and reviewing license models, this book provides a beginning-to-end guide to mastering the technical backend of this product, covering both out-of-the-box settings and customization techniques. By the end of this book, you’ll have gained a deep understanding of the Experience Cloud data model and customization options to create engaging, user-centric digital experiences that deliver value to your organization and stakeholders.