ISBN-10:
1484234499
ISBN-13:
9781484234495
Pub. Date:
03/29/2018
Publisher:
Apress
Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples

Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples

by Sayan Mukhopadhyay

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Overview







Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis.


After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects.


What You Will Learn
  • Work with data analysis techniques such as classification, clustering, regression, and forecasting
  • Handle structured and unstructured data, ETL techniques, and different kinds of databases such as Neo4j, Elasticsearch, MongoDB, and MySQL
  • Examine the different big data frameworks, including Hadoop and Spark
  • Discover advanced machine learning concepts such as semi-supervised learning, deep learning, and NLP



Who This Book Is For


Data scientists and software developers interested in the field of data analytics.



Product Details

ISBN-13: 9781484234495
Publisher: Apress
Publication date: 03/29/2018
Edition description: 1st ed.
Pages: 186
Sales rank: 659,840
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author


Sayan Mukhopadhyay in his 13+ years industry experience has been associated with companies such as Credit-Suisse, PayPal, CA Technology, CSC, and Mphasis. He has a deep understanding of the applications of data analysis in domains such as investment banking, online payments, online advertising, IT infrastructure, and retail. His area of expertise is applied high-performance computing in distributed and data-driven environments such as real-time analysis and high-frequency trading.

Table of Contents




Chapter 1: Introduction

Chapter 2: ETL with Python

Chapter 3: Supervised Learning with Python

Chapter 4: Unsupervised Learning with Python

Chapter 5: Deep Learning & Neural Networks

Chapter 6: Time Series Analysis

Chapter 7: Python in Emerging Technologies

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