This course Provides instruction on the processes and practice of data science, including machine learning and natural language processing. Included are: tools and programming languages (Python, IPython, Mahout, Pig, NumPy, pandas, SciPy, Scikit-learn), the Natural Language Toolkit (NLTK), and Spark MLlib.
This 4-day training course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Apache Pig and Apache Hive, and developing applications on Apache Spark. Topics include: Essential understanding of HDP & its capabilities, Hadoop, YARN, HDFS, MapReduce/Tez, data ingestion, using Pig and Hive to perform data analytics on Big Data and an introduction to Spark Core, Spark SQL, Apache Zeppelin, and additional Spark features.
This 5-day training course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Apache Pig and Apache Hive, and developing applications on Apache Spark. Topics include: Essential understanding of Big Data & its capabilities, Hadoop, YARN, HDFS, MapReduce/Tez, data ingestion, using Pig and Hive to perform data analytics on Big Data and an introduction to Spark Core, Spark SQL, Apache Zeppelin, and additional Spark features.
This course is designed as an entry point for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Spark. Topics include: An overview of the Hortonworks Data Platform (HDP), including HDFS and YARN; using Spark Core APIs for interactive data exploration; Spark SQL and DataFrame operations; Spark Streaming and DStream operations; data visualization, building and deploying Spark applications; and an introduction to the Spark Machine Learning Library.
İnceleThis course provides instruction on the theory and practice of data science, including machine learning and natural language processing. This course introduces many of the core concepts behind today’s most commonly used algorithms and introducing them in practical applications. We’ll discuss concepts and key algorithms in all of the major areas – Classification, Regression, Clustering, Dimensionality Reduction, including a primer on Neural Networks. We’ll focus on both single-server tools and frameworks (Python, NumPy, pandas, SciPy, Scikit-learn, NLTK, TensorFlow Jupyter) as well as large-scale tools and frameworks (Spark MLlib, Stanford CoreNLP, TensorFlowOnSpark/Horovod/MLeap, Apache Zeppelin).
This 5-day training course is designed for primarily for systems administrators and platform architects who need to understand CDH cluster capabilities, and manage CDH clusters. Topics include: Understanding CDH capabilities, Apache Hadoop, Apache YARN, HDFS, and other Hadoop ecosystem components. Students will understand how to administer, manage, and monitor CDH clusters.