by Harveen Singh Chadha | Released January 2019 | ISBN: 9781789534900

Dive into Neural Networks by solving real-world datasets using TensorflowAbout This VideoYou'll be able to solve everyday data problems quickly and easily, such as automating text processing and classifying images.Master deep learning, one of the most powerful technologies, to predict, classify, and translate.Acquire the knowledge and hands-on skills you'll need to apply deep learning for classification, which you can apply to a range of problem in the finance, healthcare, and other areas.In DetailEver wondered how you can solve everyday data problems quickly and easily like automating text processing, classifying images, and predicting results? Neural networks and Tensorflow, one of the most powerful technologies, will come to your rescue. These are important technologies for data scientists to know because they are often more powerful than traditional machine learning techniques.In this course, you'll use neural nets to solve business and other real-world problems and make predictions quickly and easily. You'll program a machine to identify a human face, predict stock market prices, and process text as part of Natural Language Processing (NLP). You'll also gain experience using generative models and autoencoders to create artwork and enhance images.By the end of this course, you will be able to tackle a range of challenges beyond this course and will have a fair understanding of how you can use the power of TensorFlow to train neural networks of varying complexities, without any hassle.All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Hands-On-Neural-Network-Programming-with-TensorFlowDownloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you. Show and hide more

1. Chapter 1 : Artificial Neural Networks
   • The Course Overview 00:03:06
   • Introduction To Neural Networks 00:05:23
   • Setting Up Environment 00:05:16
   • Introduction To TensorFlow 00:04:58
   • TensorFlow Installation 00:01:52
2. Chapter 2 : Neural Networks for Classification
   • Multilayer Perceptron Neural Network 00:02:51
   • Forward Propagation & Loss Functions 00:05:05
   • Backpropagation 00:03:46
   • Creating First Neural Network to Predict Fraud 00:15:53
   • Testing Neural Network to Predict Fraud 00:02:56
3. Chapter 3 : Use Convolutional Neural Networks (CNNs) to Identify Faces
   • Introduction To Convolutional Neural Networks 00:11:25
   • Training a Convolution Neural Network 00:16:11
   • Testing a Convolution Neural Network 00:02:19
4. Chapter 4 : Use Recurrent Neural Networks to Forecast the Stock Market
   • Introduction To Recurrent Neural Networks 00:05:05
   • Training a Recurrent Neural Network 00:08:19
   • Testing a Recurrent Neural Network 00:02:28
5. Chapter 5 : Use LSTM Networks to Classify Movie Reviews
   • Introduction To Long Short-Term Memory Network 00:04:38
   • Training an LSTM Network 00:12:49
   • Testing a Long Short-Term Memory Network 00:03:14
6. Chapter 6 : Use Generative Models to Create Artwork from Images
   • Introduction To Generative models 00:05:04
   • Neural Style Transfer: Basics 00:10:35
   • Results: Neural Style Transfer 00:07:57
7. Chapter 7 : Use Autoencoders to Colorize Images
   • Introduction To Autoencoders 00:05:55
   • Autoencoder in TensorFlow 00:15:04
   • Training & Testing a Autoencoder 00:05:15
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