Tensorflow Solutions for Data [Video]

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Tensorflow Solutions for Data [Video]

Will Ballard
Friday, January 19, 2018

Use Tensorflow's capabilities to perform efficient deep learning on Data sets

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Video Details

ISBN 139781788475488

Course Length1 hour and 30 minutes

Video Description

In this video you'll work with categorical data to predict loan performance. Categorical, structured data often appears in spreadsheets and relational databases, common data sources in business. This technique can be used to effectively predict performance or detect potential fraud.

You will also work with recurrent neural networks, which generate realistic test and placeholder data. This is useful to fill in systems with synthetic test data to simulate load and test the breadth of a working system andpredict one column from the others.

Style and Approach

This course takes a step-by-step approach, helping you explore all the functioning of TensorFlow.

Tables

The Course Overview

Setting up Your Environment

Importing CSV/SQL into Pandas

Generating Column Set -> Column Training and Testing

Keras Logistic Regression

TableModel Base Class

Logistic Regression

Deep Classification

Table Classification Service

Table Classification Configuration

REST API Definition

Trained Models in Docker Containers

Prediction Server in Docker Containers

Sentence Generation

The Name Generator

The Sentence Generator

A Machine Learning 'fortune'

What You Will Learn

Create data to predict loan performance
Build a RESTful API to make predictions on table data
Create a machine learning model for sentence generation
Build a system to generate realistic data

Authors

Will Ballard

Will Ballard serves as Chief Technology Officer at GLG and is responsible for the Engineering and IT organizations.

Prior to joining GLG, Will was the Executive Vice President of Technology and Engineering at Demand Media. Before that, he was Vice President and Chief Technology Officer of Pluck, through its acquisition by Demand Media. At both organizations, Will managed large teams of engineers responsible for software architecture, design, development, and quality assurance.

He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL.com, NPR, The Washington Post, and Whole Foods. Will has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works.com (now Bank of America).

Will graduated Magna Cum Laude with a BS in Mathematics from Claremont McKenna College.

https://github.com/wballard/kerasvideo

https://github.com/wballard/kerasvideo-server

Tables

The Course Overview

Setting up Your Environment

Importing CSV/SQL into Pandas

Generating Column Set -> Column Training and Testing

Keras Logistic Regression

TableModel Base Class

Logistic Regression

Deep Classification

Table Classification Service

Table Classification Configuration

REST API Definition