Deep Learning with Python

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.

When machine learning engineers work with data sets, they may find the results aren't as good as they need. Instead of improving the model or collecting more data, they can use the feature engineering process to help improve results by modifying the data's features to better capture the nature of the problem. This practical guide to feature engineering is an essential addition to any data scientist's or machine learning engineer's toolbox, providing new ideas on how to improve the performance of a machine learning solution. Beginning with the basic concepts and techniques, the text builds up to a unique cross-domain approach that spans data on graphs, texts, time series, and images, with fully worked out case studies. Key topics include binning, out-of-fold estimation, feature selection, dimensionality reduction, and encoding variable-length data. The full source code for the case studies is available on a companion website as Python Jupyter notebooks.

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for grad

Dive deep with Gail Gibbons as she explains the mechanics and discoveries of deep-sea exploration.Dive deep with Gail Gibbons as she explains the mechanics and discoveries of deep-sea exploration.Dive

全書以“計算思維”培養為目標，貫穿理解和運用計算生態的 Python 語言教學思想，系統展示了 Python 語言學習路徑。本書分為 12 章，主要內容如下：第 1 章講解 Python 基礎知識與概念，以及 Python 的交互式解釋器 IDLE；第 2 章講解 Python 語言語法基礎；第 3 章講解Python 控制語句；第 4 章講解 Python 數據結構；第 5 章講解 Python

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficien

"Wicked for the Cthulhu Mythos" —Seanan McGuire on the Innsmouth LegacyRuthanna Emrys’ Innsmouth Legacy, which began with Winter Tide and continues with Deep Roots, confronts H. P. Lovecraft’s Cthulhu

用 Python + Keras 實踐深度學習, 解開神經網路模型的黑盒子在高階函式庫 Keras 的幫助下, 用 6 行程式就可寫一隻深度學習神經網路的程式, 建構深度學習模型就像玩樂高積木一樣, 可以輕易將各種神經網路組合在一起, 而每一種模型可用來解決不同的問題。正宗 Keras 大神著作，正體中文版重磅登場本書為 Keras 之父 François Chollet 親自撰寫, 詳細解說神經

《Python程序設計》由淺入深、循序漸進地通過大量實例闡述了Python語言的基礎知識，同時介紹如何使用Python來解決科學計算問題，以及如何使用Python面向對象編程，還介紹了很多Python的應用技術。《Python程序設計》共9章，第1章主要是Python語言概述，第2章介紹Python的基本元素，第3章介紹Python語言的流程控制和循環語句，第4章介紹Python函數的定義與使用，

Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion an

This book covers machine learning, one of the hottest topics in more recent years. With computing power increasing exponentially and costs decreasing at the same time, there is no better time for mach

本書通過大量實例，全面、系統、深入地講解了Python編程基礎及應用開發。主要包括： Python概述及開發環境、Python編程基礎、Python函數及模塊、面向對象編程、 Python界面設計、Python數據庫編程、Python網絡編程、Python網站開發、Python繪圖與圖像處理、Python科學計算。

Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday de

Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight in

Dive deep with GAIL GIBBONS as she explains the mechanics and discoveries of deep-sea exploration.Dive deep with Gail Gibbons as she explains the mechanics and discoveries of deep-sea exploration.The

?Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging

In Coding with Python, you can talk with turtles, travel to South America, draw a flower, and create a caterpillar without paper, pencils, or paint.Easy-to-follow, step-by-step instructions will guide

創客與學習程式語言的風潮雙雙來臨, 本書結合創客與程式語言學習, 從培養邏輯思考起步，逐步學會簡單、易懂的 Python 語法, 並且利用 Python 來寫程式控制硬體, 創造有趣的創客應用。本套件總共包含 13 個實驗, 例如： ● 光感應自動電燈 ● LED 呼吸燈 ● 霹靂車跑馬燈 ● 電子鋼琴 ● 氣象預報站Learning by doing, 從做中學才能實際體驗, 在看得到效果的創客

Written for developers with a background in any high-level language, Introduction to Python and Data Science for Programmers explores the Python language and Python APIs in depth, applying the Deitels

This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fail

Move from zero knowledge of programming to comfortably writing small to medium-sized programs in Python. Fully updated for Python 3, with code and examples throughout, the book explains Python coding

This volume provides an overview of research from the learning sciences into understanding, enhancing, and measuring "deep comprehension" from a psychological, educational, and psychometric perspectiv

This volume provides an overview of research from the learning sciences into understanding, enhancing, and measuring "deep comprehension" from a psychological, educational, and psychometric perspectiv

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

A visual step-by-step guide to writing code in Python.Beginners and experienced programmers can use Python to build and play computer games, from mind-bending brainteasers to crazy action games with e

Program a graphical adventure game in this hands-on, beginner-friendly introduction to coding in the Python language.Launch into coding with Mission: Python, a space-themed guide to building a complet

A Concise Introduction to Programming in Python, Second Edition provides a hands-on and accessible introduction to writing software in Python, with no prior programming experience required.The Second

A Concise Introduction to Programming in Python, Second Edition provides a hands-on and accessible introduction to writing software in Python, with no prior programming experience required.The Second

An indispensable collection of practical tips and real-world advice for tackling common Python problems and taking your code to the next level. Features interviews with high-profile Python developers

Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Da

With the idea of “deep learning” having now become the key to this new generation of solutions, major technological players in the business intelligence sector have taken an interest in the applicatio

This book provides readers with an in-depth discussion of circuit simulation, combining basic electrical engineering circuit theory with Python programming. It fills an information gap by describing t

Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex p

The easy way to learn programming fundamentals with Python Python is a remarkably powerful and dynamic programming language that's used in a wide variety of application domains. Some of its key distin

Learn programming with Python by creating a text adventure. This book will teach you the fundamentals of programming, how to organize code, and some coding best practices. By the end of the book, you

Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related.

In Cracking Codes with Python, you’ll learn how to program in Python while making and breaking ciphers, which are used to encrypt secret messages. (No programming experience required!).After a quick c

Looking for complete instructions on manipulating, processing, cleaning, and crunching structured data in Python? The second edition of this hands-on guide—updated for Python 3.5 and Pandas 1.0—is packed with practical cases studies that show you how to effectively solve a broad set of data analysis problems, using Python libraries such as NumPy, pandas, matplotlib, and IPython.Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive applications. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.

This tutorial teaches everything you need to get started with Python programming for the fast-growing field of data analysis. Daniel Chen tightly links each new concept with easy-to-apply, relevant ex

In her second collection of poetry, Learning to See in Three Dimensions, Pamela Spiro Wagner takes us deep into an exploration of the human condition by delving into the worlds of relationships, relig