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Angular and deep learning /
"As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic deep learning concepts and incorporate that knowledge into Angular 10 applications. It is intended to be a fast-paced introduction to some basic features of deep learning and an overview of...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Dulles, Virginia :
Mercury Learning and Information,
[2021]
|
| Colección: | Pocket primer.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mi 4500 | ||
|---|---|---|---|
| 001 | EBSCO_on1269353270 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr |n||||||||| | ||
| 008 | 210314s2021 vaua o 001 0 eng d | ||
| 040 | |a INT |b eng |c INT |d OCLCO |d OCLCF |d N$T |d OCLCO |d OCLCQ |d OCLCO | ||
| 020 | |a 9781683924715 |q (electronic bk.) | ||
| 020 | |a 1683924711 |q (electronic bk.) | ||
| 020 | |a 9781683924722 |q (electronic bk.) | ||
| 020 | |a 168392472X |q (electronic bk.) | ||
| 020 | |z 9781683924739 | ||
| 020 | |z 1683924738 | ||
| 035 | |a (OCoLC)1269353270 | ||
| 050 | 4 | |a QA76.76.A54 |b C36 2021eb | |
| 082 | 0 | 4 | |a 006.7/6 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Campesato, Oswald, |e author. | |
| 245 | 1 | 0 | |a Angular and deep learning / |c Oswald Campesato. |
| 264 | 1 | |a Dulles, Virginia : |b Mercury Learning and Information, |c [2021] | |
| 300 | |a 1 online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Pocket primer | |
| 500 | |a Includes index. | ||
| 520 | |a "As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic deep learning concepts and incorporate that knowledge into Angular 10 applications. It is intended to be a fast-paced introduction to some basic features of deep learning and an overview of several popular deep learning classifiers. The book includes code samples and numerous figures and covers topics such as Angular 10 functionality, basic deep learning concepts, classification algorithms, TensorFlow, and Keras. Companion files with code and color figures are included"--Back cover. | ||
| 505 | 0 | 0 | |a Machine generated contents note: |g 1. |t Quick Introduction To Angular -- |t What You Need to Understand for Angular Applications -- |t High-Level View of Angular -- |t High-Level View of Angular Applications -- |t Angular CLI -- |t Features of the Angular CLI (optional) -- |t Hello World Angular Application -- |t Contents of the Three Main Files -- |t index.html Web Page -- |t Exporting and Importing Packages and Classes (optional) -- |t Working with Components in Angular -- |t Syntax, Attributes, and Properties in Angular -- |t Angular Lifecycle Methods -- |t Simple Example of Angular Lifecycle Methods -- |t CSS3 Animation Effects in Angular -- |t Animation Effects via the "Angular Way" -- |t Basic SVG Example in Angular -- |t Detecting Mouse Positions in Angular Applications -- |t Angular and Follow-the-Mouse in SVG -- |t Angular and SVG Charts -- |t D3 Animation and Angular -- |t Summary -- |g 2. |t UI Controls, User Input, And Pipes -- |t ngFor Directive in Angular -- |t Displaying a Button in Angular -- |t Angular and Radio Buttons -- |t Adding Items to a List in Angular -- |t Deleting Items from a List in Angular -- |t Angular Directives and Child Components -- |t Constructor and Storing State in Angular -- |t Conditional Logic in Angular -- |t Handling User Input -- |t Click Events in Multiple Components -- |t Working with @Input, @Output, and EventEmitter -- |t Presentational Components -- |t Working with Pipes in Angular -- |t Creating a Custom Angular Pipe -- |t Reading JSON Data via an Observable in Angular -- |t Upgrading Code from Earlier Angular Versions -- |t Reading Multiple Files with JSON Data in Angular -- |t Reading CSV Files in Angular -- |t Summary -- |g 3. |t Forms And Services -- |t Overview of Angular Forms -- |t Angular Form Example -- |t Angular Forms with FormBuilder -- |t Angular Reactive Forms -- |t Other Form Features in Angular -- |t What are Angular Services? -- |t Angular Service Example -- |t Service with an EventEmitter -- |t Searching for a GitHub User -- |t Other Service-related Use Cases -- |t Flickr Image Search Using jQuery and Angular -- |t HTTP GET Requests with a Simple Server -- |t HTTP POST Requests with a Simple Server -- |t SVG Line Plot from Simulated Data in Angular (optional) -- |t Summary -- |g 4. |t Deep Learning Introduction -- |t Keras and the xor Function -- |t What is Deep Learning? -- |t What are Perceptrons? -- |t Anatomy of an Artificial Neural Network (ANN) -- |t What is a Multilayer Perceptron (MLP)? -- |t How are Datapoints Correctly Classified? -- |t High-Level View of CNNs -- |t Displaying an Image in the MNIST Dataset -- |t Keras and the Mnist Dataset -- |t Keras, CNNs, and the Mnist Dataset -- |t CNNS with Audio Signals -- |t Summary -- |g 5. |t Deep Learning: Rnns And LSTMs -- |t What is an RNN? -- |t Working with RNNs and Keras -- |t Working with Keras, RNNs, and MNIST -- |t Working with TensorFlow and RNNs (Optional) -- |t What is an LSTM? -- |t Working with TensorFlow and LSTMs (Optional) -- |t What are GRUs? -- |t What are Autoencoders? -- |t What are GANs? -- |t Creating a GAN -- |t Summary -- |g 6. |t Angular And Tensorflow.JS -- |t What is TensorFlowjs? -- |t Working with Tensors in TensorFlowjs -- |t Machine Learning APIs in TensorFlowjs -- |t Linear Regression with TensorFlowjs -- |t Angular, TensorFlowjs, and Linear Regression -- |t Creating Line Graphs in tfjs-vis -- |t Creating Bar Charts in tfjs-vis -- |t Creating Scatter Plots in tfjs-vis -- |t Creating Histograms in tfjs-vis -- |t Creating Heat Maps in tfjs-vis -- |t TensorFlowjs, tfjs-vis, and Linear Regression -- |t MNIST Dataset -- |t Displaying MNIST Images -- |t Training a Model with the CIFAR10 Dataset (optional) -- |t Deep Learning and the MNIST Dataset -- |t Angular, Deep Learning, and the MNIST Dataset -- |t Summary -- |t APPENDICES -- |g A. |t Introduction To Keras -- |g B. |t Introduction To TF 2 -- |g C. |t TF 2 Datasets. |
| 588 | |a Description based on print version record. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 630 | 0 | 0 | |a AngularJS (Software framework) |
| 630 | 0 | 7 | |a AngularJS (Software framework) |2 fast |
| 650 | 0 | |a JavaScript (Computer program language) | |
| 650 | 0 | |a TypeScript (Computer program language) | |
| 650 | 0 | |a Web applications |x Development. | |
| 650 | 0 | |a Application software |x Development. | |
| 650 | 0 | |a Web applications |x Programming. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 6 | |a JavaScript (Langage de programmation) | |
| 650 | 6 | |a TypeScript (Langage de programmation) | |
| 650 | 6 | |a Applications Web |x Développement. | |
| 650 | 6 | |a Logiciels d'application |x Développement. | |
| 650 | 6 | |a Applications Web |x Programmation. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a Application software |x Development |2 fast | |
| 650 | 7 | |a JavaScript (Computer program language) |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a TypeScript (Computer program language) |2 fast | |
| 776 | 0 | 8 | |i Print version: |z 9781683924739 |z 1683924738 |
| 830 | 0 | |a Pocket primer. | |
| 856 | 4 | 0 | |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2661228 |z Texto completo |
| 938 | |a EBSCOhost |b EBSC |n 2661228 | ||
| 994 | |a 92 |b IZTAP | ||