Learn the basics of Google’s open-source framework Tensorflow to create your own custom machine learning models for tasks such as prediction and classification.
We will give you a practical introduction to Tensorflow’s dataflow paradigm and how to use the Core Tensorflow API to give you full control over the type of models you create.
You will learn:
• What Tensorflow is and its basic components
• What Tensorflow can be used for
• Tensorflow’s dataflow paradigm
• How to build a computational graph in Tensorflow
• How to evaluate graphical nodes
• How to use Tensorflow’s Optimizer
Please be on time and bring your laptop. Food and drinks will be served.
Complete Syllabus Lesson 1: Apache Spark, PySpark, and Zeppelin Intro
Lesson 2: Introduction to TensorFlow
Lesson 3: Machine Learning in TensorFlow
Lesson 4: Deployment of Kubernetes
Lesson 5: TensorFlow and Kubernets in the Cloud
Lesson 6: Putting it all Together