Understanding the Foundations of TensorFlow
Understanding the Foundations of TensorFlow
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours | 328 MB
Genre: eLearning | Language: English
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Deep Learning with TensorFlow

Deep Learning with TensorFlow
MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 6 Hours | 6.82 GB
Genre: eLearning | Language: English

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Deep Learning with TensorFlow LiveLessons By Jon Krohn
Deep Learning with TensorFlow LiveLessons By Jon Krohn
MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 6 Hours | 6.82 GB
Genre: eLearning | Language: English

Deep Learning with TensorFlow LiveLessons is an introduction to Deep Learning that bring the revolutionary machine-learning approach to life with interactive demos from the most popular Deep Learning library, TensorFlow, and its high-level API, Keras.
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Building Regression Models Using TensorFlow
Building Regression Models Using TensorFlow
Size: 267.61 MB | Duration: 2 hrs 38 mins | Video: AVC (.mp4) 1024x768 30fps | Audio: AAC 44KHz 2ch
Genre: eLearning | Level: Intermediate | Language: English | + Exercise files
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Packt Publishing - Deep Learning with TensorFlow

Packt Publishing - Deep Learning with TensorFlow
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours | 430 MB
Genre: eLearning | Language: English

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Learning Path: TensorFlow-Slim for Complex Model Building and Training

Learning Path: TensorFlow-Slim for Complex Model Building and Training
.MP4, AVC, 580 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 2+ hours | 848 MB
Instructor: Marvin Bertin
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Packt Publishing - Learning Path - TensorFlow - The Road to TensorFlow Second Edition

Packt Publishing - Learning Path - TensorFlow - The Road to TensorFlow Second Edition
English | Size: 1.90 GB
Category: CBTS

It can be hard to get started with machine learning, particularly as new frameworks like TensorFlow start to gain traction across enterprise companies. TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
This Learning Path begins by covering everything you need to know about Python. We then move on to understand deep learning as implemented by Python and TensorFlow. Finally, we solve common commercial machine learning problems using TensorFlow.
If you have no prior exposure to one of the most important trends impacting how we do data science in the next few years, this Learning Path will help you get up to speed.
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O'Reilly - Introduction to Computer Vision with TensorFlow

O'Reilly - Introduction to Computer Vision with TensorFlow
English | Size: 988.56 MB
Category: CBTS

This course provides an introduction to using deep learning models to solve computer vision tasks in TensorFlow and is focused on the work horse of deep learning image models: the convolutional neural network.

Expert Lucas Adams teaches you how to get these models up and running fast, especially in domains with limited computing resources or training data, and shows you how to modify the architecture of a neural network to make the model specialized to different tasks. Learners should be familiar with basic deep learning concepts like the multilayer perceptron, linear algebra, Jupyter notebooks, and the basics of building and running TensorFlow programs.
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O'Reilly - Introduction to Deep Learning Models With TensorFlow
O'Reilly - Introduction to Deep Learning Models With TensorFlow
English | Size: 162.29 MB
Category: Tutorial

Learn How to Work With TensorFlow to Create and Run a TensorFlow Graph, and Build a Deep Learning Model.
TensorFlow is by far the most popular deep learning software package available today. This training covers all of the essentials of TensorFlow; and provides you with hands-on experience building a deep learning model using the TensorFlow library. Every line of code written during the course is analyzed to help you understand what can be a complicated process.
The lessons look at the key mathematical foundations of deep learning models, giving you insight into what makes these techniques work. Created for software engineers and budding data scientists, the course requires basic familiarity with Python programming; as well as statistics concepts such as linear and logistic regression, machine learning concepts like classification, and linear algebra. Jupyter Notebook is used to write and run code.
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Learning Path - TensorFlow: The Road to TensorFlow Second Edition

Learning Path - TensorFlow: The Road to TensorFlow Second Edition
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 8 Hours | 1.90 GB
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