Building Machine Learning Solutions with Tensorflow (Path)

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[img]https://i.imgur.com/tpdq8xX.png[/img]
[b]Building Machine Learning Solutions with Tensorflow (Path)[/b]
Jerry Kurata (et al.) | Duration: 28h 00m | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 4,23 GB | Language: English
TensorFlow is an open-source machine learning software library developed Google.

Since it was released in 2015, it has become one of the most widely-used machine learning libraries. This skill will teach you how to implement the machine learning workflow using TensorFlow, and apply the library from Python to solve simple and complex machine learning problems.

Build your first TensorFlow project, and create regression, classification, and clustering models.
Debug and deploy your TensorFlow model.
Use TensorFlow across an array of high-level cognitive computing problems, such as sennt analysis, language modeling, image recognition, and predictive analytics.

Courses in this path

A1. TensorFlow. Getting Started (Jerry Kurata, 2017)
A2. Understanding the Foundations of TensorFlow (Janani Ravi, 2017)
A3. Building Regression Models Using TensorFlow (Vitthal Srinivasan, 2017)
A4. Building Classification Models with TensorFlow (Janani Ravi, 2017)
A5. Building Unsupervised Learning Models with TensorFlow (Janani Ravi, 2017)
B1. Debugging and Monitoring TensorFlow Programs (Janani Ravi, 2018)
B2. Deploying TensorFlow Models to AWS, Azure, and the GCP (Janani Ravi, 2018)
C1. Language Modeling with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2018)
C2. Implementing Image Recognition Systems with TensorFlow (Jon Flanders, 2019)
C3. Implementing Predictive Analytics with TensorFlow (Justin Flett, 2018)
C4. Sennt Analysis with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2017)

HomePage:

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