03786nam 22006975 450 991063247520332120251008145137.09781484280058148428005910.1007/978-1-4842-8005-8(MiAaPQ)EBC7147130(Au-PeEL)EBL7147130(CKB)25483682800041(OCoLC)1351999040(OCoLC-P)1351999040(DE-He213)978-1-4842-8005-8(PPN)26635369X(CaSebORM)9781484280058(Perlego)4514126(EXLCZ)992548368280004120221125d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdvanced Data Analytics Using Python With Architectural Patterns, Text and Image Classification, and Optimization Techniques /by Sayan Mukhopadhyay, Pratip Samanta2nd ed. 2023.Berkeley, CA :Apress :Imprint: Apress,2023.1 online resource (259 pages)Includes index.9781484280041 1484280040 Chapter 1: Overview of Python Language -- Chapter 2: ETL with Python -- Chapter 3: Supervised Learning and Unsupervised Learning with Python -- Chapter 4: Clustering with Python -- Chapter 5: Deep Learning & Neural Networks -- Chapter 6: Time Series Analysis -- Chapter 7: Analytics in Scale.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. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics withreinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. You will: Build intelligent systems for enterprise Review time series analysis, classifications, regression, and clustering Explore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analytics Understand Covers design patterns in Python .Artificial intelligenceData processingMachine learningPython (Computer program language)Artificial intelligenceData ScienceMachine LearningPythonArtificial IntelligenceArtificial intelligenceData processing.Machine learning.Python (Computer program language)Artificial intelligence.Data Science.Machine Learning.Python.Artificial Intelligence.006.312Mukhopadhyay Sayan1062767Samanta PratipMiAaPQMiAaPQMiAaPQBOOK9910632475203321Advanced Data Analytics Using Python2982346UNINA