Analiza danych

Te małe seksowne cyferki. Jak rozwinąć biznes przy użyciu danych, które już mamy

Paul Brown, Dimitri Maex

Czy możesz sobie wyobrazić, że jesteś w stanie zidentyfikować klientów przynoszących największe zyski, wypracować lepszą strategię komunikowania się z nimi i zainspirować ich, aby kupowali więcej? A więc, naprawdę możesz to zrobić. A najlepsze jest to, że możesz to osiągnąć używając danych, które już masz. Wszystko, co robimy, tworzy dane. Za każdym razem, gdy ktoś ogląda coś w sieci, szuka w Google lub nawet przegląda sieć w swoim telefonie, tworzona jest kolejna cząstka danych, które mogą pomóc nam zrozumieć i przewidzieć zachowanie konsumentów. Rewolucja w analizowaniu danych właśnie się toczy i metody oraz narzędzia radzące sobie z tym „potopem danych” stają się coraz prostsze i mniej kosztowne, a jednocześnie bardziej precyzyjne, niż kiedykolwiek wcześniej.  Dimitri Maex, Managing Director globalnej agencji reklamowej OgilvyOne New York i mózg praktyki analitycznej stosowanej w agencji pokazuje, jak możemy przekształcić swoje dane – te małe seksowne cyferki, które mogą zapewnić więcej zysków naszemu biznesowi – w skuteczne strategie prawdziwego wzrostu. W jasnym, przejrzystym stylu wyjaśnia, jak: • Ustalić, którzy klienci mają największy potencjał zwiększenia wartości, po których można spodziewać się większych zakupów, a którzy nie są warci targetowania. • Alokować zasoby marketingowe w najlepszy możliwy sposób. • Przewidzieć, jakich produktów lub usług klienci będą potrzebować w przyszłości. • Zoptymalizować swoją obecność w sieci, aby uzyskać największy zwrot z wyszukiwania. Lektura obowiązkowa dla marketerów starających się uzyskać najwyższy zwrot z inwestycji, właścicieli małych firm pragnących rosnąć szybciej lub kreatywnych twórców pragnących poznać reakcję na swoje działania – i nie tylko.

Tech Trends of the 4th Industrial Revolution. Navigating the Future of Technology in Business

Mercury Learning and Information, D. Pyo, J....

The term 4th Industrial Revolution is often mentioned in the media, but public understanding of its technologies lags behind their rapid development. This book bridges the gap, explaining essential technologies like IoT, blockchain, AI, cloud computing, and big data. It aims to enhance comprehension by minimizing technical content.The book introduces key technologies and their applications, emphasizing their importance in contemporary business models. Readers will find accessible descriptions and practical examples to aid understanding. Covering topics and trends vital for modern business, this book ensures readers grasp the technological landscape shaping the future.Throughout the book, you'll explore how these technologies are revolutionizing industries and their integration into business strategies. This journey provides a comprehensive understanding of the 4th Industrial Revolution, equipping readers with the knowledge needed to navigate and leverage these advancements effectively.

TensorFlow 1.x Deep Learning Cookbook. Over 90 unique recipes to solve artificial-intelligence driven problems with Python

Antonio Gulli, Amita Kapoor

Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve real-life problems in the artificial intelligence domain.In this book, you will learn how to efficiently use TensorFlow, Google’s open source framework for deep learning. You will implement different deep learning networks, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs), with easy-to-follow standalone recipes. You will learn how to use TensorFlow with Keras as the backend. You will learn how different DNNs perform onsome popularly used datasets, such as MNIST, CIFAR-10, and Youtube8m. You will not only learn about the different mobile and embedded platforms supported by TensorFlow, but also how to set up cloud platforms for deep learning applications. You will also get a sneak peek at TPU architecture and how it will affect the future of DNNs.By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning,GANs, and autoencoders.

TensorFlow 2.0 Quick Start Guide. Get up to speed with the newly introduced features of TensorFlow 2.0

Tony Holdroyd

TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks.After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains.By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques.

TensorFlow Deep Learning Projects. 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning

Abhishek Thakur, Alberto Boschetti, Luca Massaron, Alexey...

TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games.By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.

TensorFlow Machine Learning Cookbook. Over 60 practical recipes to help you master Google’s TensorFlow machine learning library

Nick McClure

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow.This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.

Teradata Cookbook. Over 85 recipes to implement efficient data warehousing solutions

Abhinav Khandelwal, Rajsekhar Bhamidipati

Teradata is an enterprise software company that develops and sells its eponymous relational database management system (RDBMS), which is considered to be a leading data warehousing solutions and provides data management solutions for analytics. This book will help you get all the practical information you need for the creation and implementation of your data warehousing solution using Teradata.The book begins with recipes on quickly setting up a development environment so you can work with different types of data structuring and manipulation function. You will tackle all problems related to efficient querying, stored procedure searching, and navigation techniques. Additionally, you’ll master various administrative tasks such as user and security management, workload management, high availability, performance tuning, and monitoring.This book is designed to take you through the best practices of performing the real daily tasks of a Teradata DBA, and will help you tackle any problem you might encounter in the process.

Text Analytics for Business Decisions. Mastering Techniques for Insightful Data Interpretation through a Case Study Approach

Mercury Learning and Information, Andres Fortino

This book leverages advanced techniques and tools in data science to extend data analysis from numeric and categorical data to textual data. Designed for business analysts, it uses a case study approach to teach skills in extracting insights from text data, supporting business decision-making. Exercises primarily use Excel and R, covering techniques from basic text analytics to sophisticated methods like topic extraction and text similarity scoring.The course begins with framing analytical questions and exploring analytical tool sets. It progresses through preparing data files, performing word frequency and keyword analysis, and conducting sentiment analysis. Advanced topics include visualizing text data, coding, named entity recognition, and topic recognition in documents. The book also covers text similarity scoring and the analysis of large datasets by sampling.Throughout this journey, readers will apply the CRISP-DM data mining standard, using companion files with numerous datasets for practical exercises. By the end, participants will have a comprehensive understanding of text analytics, enabling them to derive meaningful insights from textual data to inform business strategies.