TY  - BOOK
AU  - Mukhopadhyay,Sayan
TI  - Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples 
SN  - 1484234502
AV  - QA76.73.P98 
U1  - 005.133 23
PY  - 2018///
CY  - Berkeley, CA
PB  - Apress, Imprint: Apress
KW  - Python (Computer program language)
KW  - Big data
KW  - Open source software
KW  - Computer programming
KW  - Python
KW  - Big Data
KW  - Open Source
N1  - Includes index; 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
N2  - 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. You will: 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
ER  -