Deep Learning with TensorFlow
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VIDEO TUTORIAL Deep Learning with TensorFlow

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Channel the power of deep learning with Google's TensorFlow!

About This Deep Learning with TensorFlow Video course

  • Explore various possibilities with deep learning and gain amazing insights from data using Google’s brainchild—TensorFlow
  • Want to learn what more can be done with deep learning? Explore various neural networks with the help of this comprehensive guide!
  • Rich in concepts, this is an advanced guide on deep learning that will give you the background to innovate in your environment

Deep Learning with TensorFlow In Detail

Deep learning is the intersection of statistics, artificial intelligence, and data to build accurate models and TensorFlow is one of the newest and most comprehensive libraries for implementing deep learning.

With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. This video course is your guide to exploring the possibilities with deep learning; it will enable you to understand data like never before!

With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data.

With this video tutorial, you will dig your teeth deeper into the hidden layers of abstraction using raw data. This course will offer you various complex algorithms for deep learning and various examples that use these deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data. During the video course, you will come across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, high level interfaces, and more.

With the help of novel practical examples, you will become an ace at advanced multilayer networks, image recognition, and beyond.

What will you learn in this course?

Course plan
Chapter 1
Getting Started
Chapter 2
Deep Neural Networks
Chapter 3
Convolutional Neural Networks
Chapter 4
Recurrent Neural Networks
Chapter 5
Wrapping Up

Detailed course plan

Chapter 1 : Getting Started
Lesson 1The Course Overview
Lesson 2Installing TensorFlow
Lesson 3Simple Computations
Lesson 4Logistic Regression Model Building
Lesson 5Logistic Regression Training
Chapter 2 : Deep Neural Networks
Lesson 1Basic Neural Nets
Lesson 2Single Hidden Layer Model
Lesson 3Single Hidden Layer Explained
Lesson 4Multiple Hidden Layer Model
Lesson 5Multiple Hidden Layer Results
Chapter 3 : Convolutional Neural Networks
Lesson 1Convolutional Layer Motivation
Lesson 2Convolutional Layer Application
Lesson 3Pooling Layer Motivation
Lesson 4Pooling Layer Application
Lesson 5Deep CNN
Lesson 6Deeper CNN
Lesson 7Wrapping Up Deep CNN
Chapter 4 : Recurrent Neural Networks
Lesson 1Introducing Recurrent Neural Networks
Lesson 2Skflow
Lesson 3RNNs in skflow
Chapter 5 : Wrapping Up
Lesson 1Research Evaluation
Lesson 2The Future of TensorFlow

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