The Art of Conducting (Da Capo Press music reprint series) [Mar 01, 1975] Bowles, Michael and Boult, Adrian ... 0306707187

The Art Of Conducting

Arts & Photography

Bowles, Michael

Music

Da Capo Press

Pages have no markings or folds. Binding is solid. Dust jacket has fairly heavy wear around the edges. Poly bagged for extra protection.

Schooling in Capitalist America: Educational Reform and the Contradictions of Economic Life

Education & Teaching

Schools & Teaching

Basic Books

Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. <ul>
<li>Predict outcomes using linear and ensemble algorithm families</li> <li>Build predictive models that solve a range of simple and complex problems</li> <li>Apply core machine learning algorithms using Python</li> <li>Use sample code directly to build custom solutions</li> </ul>
Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.

Machine Learning In Python W/Ws

Computers & Technology

Computer Science

wiley

Machine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves with the addition of Spark―a ML framework from the Apache foundation. By implementing Spark, machine learning students can easily process much large data sets and call the spark algorithms using ordinary Python code. Machine Learning with Spark and Python focuses on two algorithm families (linear methods and ensemble methods) that effectively predict outcomes. This type of problem covers many use cases such as what ad to place on a web page, predicting prices in securities markets, or detecting credit card fraud. The focus on two families gives enough room for full descriptions of the mechanisms at work in the algorithms. Then the code examples serve to illustrate the workings of the machinery with specific hackable code.

Machine Learning with Spark and Python: Essential Techniques for Predictive Analytics

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