Treffer: Large Scale Machine Learning with Python

About This BookDesign, engineer and deploy scalable machine learning solutions with the power of PythonTake command of Hadoop and Spark with Python for effective machine learning on a map reduce frameworkBuild state-of-the-art models and develop personalized recommendations to perform machine learning at scaleWho This Book Is ForThis book is for anyone who intends to work with large and complex data sets. Familiarity with basic Python and machine learning concepts is recommended. Working knowledge in statistics and computational mathematics would be helpful.What You Will LearnApply the most scalable machine learning algorithmsWork with modern state-of-the-art large-scale machine learning techniquesIncrease predictive accuracy with deep learning and scalable data-handling techniquesWork with a MapReduce framework in SparkApply effective machine learning algorithms with Spark and HadoopBuild powerful ensembles at scaleUse data streams to train linear and non-linear predictive models from extremely large datasets using a single machineIn DetailWith the rise of big data comes an increasing demand for computational and algorithmic efficiency. Large Scale Machine Learning with Python uncovers a new wave of machine learning algorithms that meet scalability demands together with a high predictive accuracy.First, we start with the family of machine learning algorithms that are considered scalable. With this family of algorithms, we lead you through three levels of scalability. The first level is all about speeding up algorithms that can be used on a desktop computer. We will provide tips on parallelization and memory allocation. The second level is the newer algorithms that are specifically designed for scalability and can handle bigger files. The third level is about machine learning in big data environments.We will also cover the most effective machine learning techniques on a MapReduce framework in Hadoop and Spark in Python.