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Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using;
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provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing;
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familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use;
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with some basic data mining techniques such as SQL and machine learning, and who are comfortable with Python. If you are ready to learn some;
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts;
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serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and;
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Science with Python - data mining, data analysis, data visualization, and machine learning Who This Book Is For If you are a Python;
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This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale;
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learning, and data mining-including supervised and unsupervised data mining methods-are treated in detail, as are time series forecasting, text;
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fundamentals of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis;
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of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts;
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, contemporary examples. These include natural language processing, data mining Twitter (R) for sentiment analysis, cognitive computing with IBM (R;
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Acquire and analyze data from all corners of the social web with Python About This Book * Make sense of highly unstructured social;
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the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R;
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Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data;
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with Python Machine Learning from scratch or extend your knowledge in Data Science, this is a must-have guide. Machine Learning is changing;
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Is For This book is for anyone interested in entering the data science stream with machine learning. Basic familiarity with Python is assumed;
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through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data;
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Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs;
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Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows;
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Get more from your data by creating practical machine learning systems with Python Key Features Develop your own Python-based machine;
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Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;
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Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;
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Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark;
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