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[null,"1.","Record Nr.",null,"UNINA990004164370403321"]
[null,null,"Autore",null,"Herring, Herbert"]
[null,null,"Titolo",null,"Das Problem der Affektion bei Kant : die Frange nach Gegebenheitsweise des Gegenstandes in der Kritik der reinen Vernunft und die Kant-Interpretation / Herbert Herring"]
[null,null,"Pubbl/distr/stampa",null,"Köln : Kölner Universitäts, 1953"]
[null,null,"Descrizione fisica",null,"108 p. ; 23 cm"]
[null,null,"Collana",null,"Kantstudien. Ergänzungshefte ; 67"]
[null,null,"Disciplina",null,"193"]
[null,null,"Locazione",null,"FLFBC"]
[null,null,"Collocazione",null,"P.1 7D KANT/S 350"]
[null,null,"Lingua di pubblicazione",null,"Tedesco"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910300760303321"]
[null,null,"Autore",null,"Mukhopadhyay Sayan"]
[null,null,"Titolo",null,"Advanced Data Analytics Using Python : With Machine Learning, Deep Learning and NLP Examples / / by Sayan Mukhopadhyay"]
[null,null,"Pubbl/distr/stampa",null,"Berkeley, CA : , : Apress : , : Imprint : Apress, , 2018"]
[null,null,"ISBN",null,"9781484234501"]
[{"$nulls":4},"1484234502"]
[null,null,"Edizione",null,"[1st ed. 2018.]"]
[null,null,"Descrizione fisica",null,"1 online resource (195 pages)"]
[null,null,"Disciplina",null,"005.133"]
[null,null,"Soggetti",null,"Python (Computer program language)"]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Open source software"]
[{"$nulls":4},"Computer programming"]
[{"$nulls":4},"Python"]
[{"$nulls":4},"Big Data"]
[{"$nulls":4},"Open Source"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Chapter 1: Introduction -- Chapter 2: ETL with Python -- Chapter 3: Supervised Learning with Python -- Chapter 4: Unsupervised Learning with Python -- Chapter 5: Deep Learning & Neural Networks -- Chapter 6: Time Series Analysis -- Chapter 7: Python in Emerging Technologies."]
[null,null,null,"Sommario/riassunto","Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis. After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects. You will: Work with data analysis techniques such as classification, clustering, regression, and forecasting Handle structured and unstructured data, ETL "]
[{"$nulls":4},"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."]