Natural Language Processing with Python
This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library.
This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library.
Although most concepts are relatively simple, there are many of them, and they interact with each other in unobvious ways, which is a major challenge of neural networks. But you can learn all important neural network concepts by running and examining the code in this book, with complete example programs for the three major types of neural network problems.
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
A Whirlwind Tour of Python is a fast-paced introduction to essential features of the Python language, aimed at researchers and developers who are already familiar with programming in another language. The material is particularly designed for those who wish to use Python for data science and/or scientific programming, and in this capacity serves as an introduction to my longer book, The Python Data Science Handbook.
This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science.
A comprehensive introduction to the latest forecasting methods. Examples use R with many data sets taken from the authors’ own consulting experience. In this second edition, all chapters have been updated to cover the latest research, and three new chapters have been added on dynamic regression forecasting, hierarchical forecasting and practical forecasting issues.
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. (“Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” ―Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX).