Advanced Data Analytics Using Python
With Architectural Patterns, Text and Image Classification, and Optimization Techniques
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Beschreibung
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
Explains recommendation system, algorithm trading, and PySpark with use cases and hands-on coding Explains feature engineering in images and texts with Python Covers recent advances in databases such as Neo4j, Elasticsearch, and MongoDB
Autor*in
Sayan Mukhopadhyay
Themen in »Advanced Data Analytics Using Python«
Python Machine Learning Data Analytics Deep Learning Apache Spark Natural Language Processing Reinforcement Learning Recurrent Neural Networks Time Series Elastic Search