Using TensorFlow for Intelligent Applications Classroom Live Boston, MA July 19, 2021

Price: $1,700

This course runs for a duration of 2 days.

The class will run daily from 8:30 am EST to 4:30 pm EST.

Class Location: Boston - Boston, MA.

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Description

TensorFlow is currently the most practical and accessible open-source machine learning tool for integrating intelligent features into our applications. Our organizations rely on petabytes of aggregated, structured data we’ve collected over the years. Even with good business intelligence practices, competitive position is increasingly defined by the ability to integrate an “intelligence layer” into the applications which ingest and utilize our data.

For software developers and data engineers ready to expand their silo and integrate intelligent services into applications, this TensoFlow course trains up engineering teams to build on domain expertise and design machine intelligence features using the popular TensorFlow library. TensorFlow delivers a myriad of deep learning best practices as part of its default configuration so complex machine learning just works out of the box.

TensorFlow democratizes deep learning for anyone with Python or C capability, but machine learning is not just another programming language. Our workshop allows you to learn from a live teacher, tie machine learning to value-driven use cases, and ask real-time questions in class.

Course Overview

Part 1: Overview of TensorFlow and TensorFlow libraries

  1. Using Python with TensorFlow

  2. Translating meaningful information into geometric spaces

  3. Training infrastructure

  4. Regressors

  5. Keras API

  6. Estimators and experiments

Part 2: Use cases for a machine learning service

  1. Deep learning implementation

  2. AI and macro insight opportunities

  3. Image processing use cases

  4. Predictive use cases

  5. Scoring datasets for machine learning

  6. Estimators

Part 3: Using and applying your model

  1. Defining the model

  2. Training the model

  3. Evaluating the model

  4. Prediction outputs

Part 4: Training your model

  1. Setting up the training cycle

  2. Training data

  3. Adjusting bias

  4. Weights

Part 5: Testing your model

  1. Testing overview

  2. Model values vs. output values

Part 6: Using TensorBoard to visualize model performance

  1. Loss curve

  2. Biases

  3. Examining graphs

  4. Learning rate decay

Prerequisites

This course is for individuals with intermediate experience with Python and C. Any experience with TensorFlow is also beneficial.

Other Available Dates for this Course

Virtual Classroom Live
March 17, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
May 11, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Classroom Live
May 11, 2021

Minneapolis, MN
$1,700.00
2 days    8:30 am CST - 4:30 pm CST
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Classroom Live
May 19, 2021

Minneapolis, MN
$1,700.00
2 days    8:30 am CST - 4:30 pm CST
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Virtual Classroom Live
June 23, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
July 12, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
August 24, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
September 08, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Classroom Live
September 21, 2021

Seattle, WA
$1,700.00
2 days    8:30 am PST - 4:30 pm PST
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Virtual Classroom Live
October 13, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
November 02, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
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Classroom Live
November 17, 2021

Madison, WI
$1,700.00
2 days    8:30 am CST - 4:30 pm CST
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Virtual Classroom Live
December 13, 2021

$1,700.00
2 days    8:30 am EST - 4:30 pm EST
view class details and enroll