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Machine Learning Techniques for Text. Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation

Język publikacji: angielskim
Machine Learning Techniques for Text. Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation Nikos Tsourakis - okladka książki

Machine Learning Techniques for Text. Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation Nikos Tsourakis - okladka książki

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448
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With the ever-increasing demand for machine learning and programming professionals, it's prime time to invest in the field. This book will help you in this endeavor, focusing specifically on text data and human language by steering a middle path among the various textbooks that present complicated theoretical concepts or focus disproportionately on Python code.
A good metaphor this work builds upon is the relationship between an experienced craftsperson and their trainee. Based on the current problem, the former picks a tool from the toolbox, explains its utility, and puts it into action. This approach will help you to identify at least one practical use for each method or technique presented. The content unfolds in ten chapters, each discussing one specific case study. For this reason, the book is solution-oriented. It's accompanied by Python code in the form of Jupyter notebooks to help you obtain hands-on experience. A recurring pattern in the chapters of this book is helping you get some intuition on the data and then implement and contrast various solutions.
By the end of this book, you'll be able to understand and apply various techniques with Python for text preprocessing, text representation, dimensionality reduction, machine learning, language modeling, visualization, and evaluation.
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O autorze książki

Nikos Tsourakis is a professor of computer science and business analytics at the International Institute in Geneva, Switzerland, and a research associate at the University of Geneva. He has over 20 years of experience designing, building, and evaluating intelligent systems using speech and language technologies. He has also co-authored over 50 research publications in the area. In the past, he worked as a software engineer, developing products for major telecommunication vendors. He also served as an expert for the European Commission and is currently a certified educator at the Amazon Web Services Academy. He holds a degree in electronic and computer engineering, a master's in management, and a PhD in multilingual information processing.

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