Lesson 2/6: Introductory workshop to TensorFlow
Details
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.
If you weren't in attendance for the first session, please follow the instructions in this document to set up your environment before arriving: https://docs.google.com/document/d/1ayIjeM0SUA3BuF2CTOhcsyVgL9MP13NVHkPlrw7_MSQ/edit
Please be on time and bring your laptop. Food and drinks will be served.
Itinerary:
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
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