Python data mining and machine learning in action

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic

3 comprehensive manuscripts in 1 bookMachine Learning: An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More

Gain insight into essential data science skills in a holistic manner using data engineering and associated scalable computational methods. This book covers the most popular Python 3 frameworks for bot

本書作為數據挖掘的入門讀物，基於真實的數據集進行案例實戰，使用Python數據科學庫，從數據預處理開始一步步介紹數據建模和數據挖掘的過程。主要介紹了數據挖掘的基礎知識、基本工具和實踐方法，通過循序漸進地講解算法，帶領讀者輕鬆踏上數據挖掘之旅。本書採用理論與實踐相結合的方式，呈現了如何使用邏輯回歸進行環境數據檢測，如何使用HMM進行中文分詞，如何利用卷積神經網絡識別雷達剖面圖，如何使用循環神經網絡構建聊天機器人，如何使用樸素貝葉斯算法進行破產預測，如何使用DCGAN網絡進行人臉生成等。本書也涉及神經網絡、在線學習、強化學習、深度學習和大數據處理等內容。本書以人工智能主流編程語言Python 3版本作為數據分析與挖掘實戰的應用工具，從Pyhton的基礎語法開始，陸續介紹了NumPy數值計算、Pandas數據處理、Matplotlib數據可視化、爬蟲和Sklearn數據挖掘等內容。全書共涵蓋16個常用的數據挖掘算法和機器學習實戰項目。通過學習本書內容，讀者可以掌握數據分析與挖掘的理論知識及實戰技能。

Are you stuck in getting started with machine learning with python? A Step-By-Step Guide to Learn and Master Python Machine Learning walks you through steps for getting started with Machine Learning w

Create AI applications in Python and lay the foundations for your career in data scienceKey FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail wit

This book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireles

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer

Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investmentBig Data and Machine Learning in Quantitative Investment is not just about demonstrat

Predictive Analytics has revolutionised marketing practice. It involves using many techniques from data mining, statistics, modelling, machine learning and artificial intelligence, to analyse current

"Let's practice! helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon ... Storytelling With Data'

Focuses on a new topic each week covering map skills, applying information and data, and connecting what was learnedBuilds student's confidence in geography with quick independent learning activities

Focuses on a new topic each week covering map skills, applying information and data, and connecting what was learnedBuilds student's confidence in geography with quick independent learning activities

Focuses on a new topic each week covering map skills, applying information and data, and connecting what was learnedBuilds student's confidence in geography with quick independent learning activities

Focuses on a new topic each week covering map skills, applying information and data, and connecting what was learnedBuilds student's confidence in geography with quick independent learning activities

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. Th

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scala

This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.The

The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosyste

從做中學！淺顯的對話教學！易懂的程式開發！ 帶你逐步學習Python！從簡單的程式設計到人工智慧應用程式開發都體驗得到！ 在你學習Python程式開發原理的同時，也將製作出充滿樂趣的人工智慧應用程式！ 近年來，Python是非常熱門的程式語言，尤其是在人工智慧這個領域上受到大眾的矚目。在網頁開發與資料分析上，Python的使用者數量都在持續上升中。 本書是針對Python新手所設計的書籍，不但可以

"This book identifies the role of digital technology in personalized learning, brings together research in personalized learning with a focus on cognitive, affective and metacogntive functionality of

This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not nor

Machine Learning with Spark and Python Essential Techniques for Predictive Analytics Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different ap

The Python programming language and its libraries, including pandas and scikit-learn, provide a production-grade environment to help you accomplish a broad range of machine-learning tasks. With this c

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algo

If you think of science as a puzzle, you’ll see that data is a key to unlocking it. Exemplary Evidence: Scientists and Their Data touches on the world’s many riddles—from how we see to what’s at the b

本書是《Deep Learning : 用Python進行深度學習的基礎理論實作》的續篇，將延續上一本書，繼續介紹與深度學習有關的技術。本書尤其偏重在自然語言處理及時間序列資料處理上，使用深度學習，挑戰各式各樣的問題。和上一本著作一樣，以「從零開始建構」為概念，詳盡介紹與深度學習有關的先進技術。 簡單來說，自然語言處理是指，讓電腦瞭解我們平常說話內容的技術。事實上，這種自然語言處理技術已經大大改變

Professor Volt's first time machine somehow made it to the present and must be escorted back in time as soon as possible, before it alters the course of history!

A valuable new edition of a standard referenceThe use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An In

Now in its fifth edition, this invaluable handbook provides a complete guide to the practical application of data protection law. It is fully updated and expanded to include coverage of significant de

A groundbreaking, flexible approach to computer science and data scienceThe Deitels’ Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud o

The first machine-learning guide that helps you understand customers, frame decisions, and drive value Business Data Science reveals the best ways for utilizing machine learning (ML) to mak

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to

Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use i

This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine