Machine Learning & Deep Learning Essentials with Spark and TensorFlow (TTML5508)
Explore Core Machine Learning and Deep Learning Skills, Regression, Classification, Naïve Bayes, Spark, TensorFlow, Keras, Neural Networks & More
Apache Spark, a significant component in the Hadoop Ecosystem, is a cluster computing engine used in Big Data. Building on top of the Hadoop YARN and HDFS ecosystem, offers order-of-magnitude faster processing for many in-memory computing tasks compared to Map/Reduce. It can be programmed in Java, Scala, Python, and R - the favorite languages of Data Scientists - along with SQL-based front ends.
Machine Learning & Deep Learning Essentials with Spark and TensorFlow is hands-on course designed for data scientists and software engineers new to Machine Learning. Working in a hands-on learning environment, you’ll learn how to perform Machine Learning at scale using the popular Apache Spark framework, working from the ground up, exploring Apache Spark essentials, core machine learning concepts, regressions, classifications, clustering and more.
The abundance of data and affordable cloud scale has led to an explosion of interest in Deep Learning. Google has released an excellent library called TensorFlow to open-source, allowing state-of-the-art machine learning done at scale, complete with GPU-based acceleration. In the second half of the class, you’ll dive into deep learning concepts and learn how to implement them using TensorFlow.