Advanced Data Analytics Using Python by Sayan Mukhopadhyay

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Advanced Data Analytics Using Python

Author : Sayan Mukhopadhyay
Publisher : Apress
Published : 2018-03-29
ISBN-10 : 1484234502
ISBN-13 : 9781484234501
Number of Pages : 186 Pages
Language : en


Descriptions Advanced Data Analytics Using Python

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 LearnWork with data analysis techniques such as classification, clustering, regression, and forecastingHandle structured and unstructured data, ETL techniques, and different kinds of databases such as Neo4j, Elasticsearch, MongoDB, and MySQLExamine the different big data frameworks, including Hadoop and SparkDiscover advanced machine learning concepts such as semi-supervised learning, deep learning, and NLPWho This Book Is ForData scientists and software developers interested in the field of data analytics.
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Advanced Data Science and Analytics with Python - The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported
Apress/advanced-data-analytics-using-python - Github - This repository accompanies Advanced Data Analytics Using Python by Sayan Mukhopadhyay (Apress, 2018). Download the files as a zip using the green button, or clone the repository to your machine using Git. Releases. Release v1.0 corresponds to the code in the published book, without corrections or updates. Contributions
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Advanced Data Analytics Using Python: With Architectural Patterns, Text - Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment
Advanced Data Analytics Using Python - Springer - Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment
Advanced Data Analytics Using Python - Google Books - 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
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Apress/advanced-data-analytics-python-2e - Github - This repository accompanies Advanced Data Analytics Using Python by Sayan Mukhopadhyay (Apress, 2022). Download the files as a zip using the green button, or clone the repository to your machine using Git. Releases. Release v1.0 corresponds to the code in the published book, without corrections or updates. Contributions
Advanced Data Analytics using Python [2022] | Udemy -
Advanced Data Analytics Using Python - Google Books -
Advanced Data Analytics Using Python - Springer -
Advanced Data Analytics Using Python - Springer - Web · Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using …