عنوان
پدید آورنده
موضوع
رده
QA76.73.J38 .K375 2018
QA76
.
73
.
J38
.
K375
2018
کتابخانه
محل استقرار
شابک
شابک
1788996526
شابک
178899745X
شابک
9781788996525
شابک
9781788997454
عنوان و نام پديدآور
عنوان اصلي
Java Deep Learning Projects :
نام عام مواد
[Book]
ساير اطلاعات عنواني
Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Birmingham :
نام ناشر، پخش کننده و غيره
Packt Publishing Ltd,
تاریخ نشرو بخش و غیره
2018.
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (428 pages)
يادداشت کلی
متن يادداشت
Sentiment analysis using Word2Vec and LSTM.
یادداشتهای مربوط به مندرجات
متن يادداشت
Intro; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Getting Started with Deep Learning; A soft introduction to ML; Working principles of ML algorithms; Supervised learning; Unsupervised learning; Reinforcement learning; Putting ML tasks altogether; Delving into deep learning; How did DL take ML into next level?; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.
متن يادداشت
Frequently asked questions (FAQs)Summary; Answers to FAQs; Chapter 2: Cancer Types Prediction Using Recurrent Type Networks; Deep learning in cancer genomics; Cancer genomics dataset description; Preparing programming environment; Titanic survival revisited with DL4J; Multilayer perceptron network construction; Hidden layer 1; Hidden layer 2; Output layer; Network training; Evaluating the model; Cancer type prediction using an LSTM network; Dataset preparation for training; Recurrent and LSTM networks; Dataset preparation; LSTM network construction; Network training; Evaluating the model.
متن يادداشت
Frequently asked questions (FAQs)Summary; Answers to questions; Chapter 3: Multi-Label Image Classification Using Convolutional Neural Networks; Image classification and drawbacks of DNNs; CNN architecture; Convolutional operations; Pooling and padding operations; Fully connected layer (dense layer); Multi-label image classification using CNNs; Problem description; Description of the dataset; Removing invalid images; Workflow of the overall project; Image preprocessing; Extracting image metadata; Image feature extraction; Preparing the ND4J dataset.
متن يادداشت
Neural network architecturesDeep neural networks; Multilayer Perceptron; Deep belief networks; Autoencoders; Convolutional neural networks; Recurrent neural networks ; Emergent architectures; Residual neural networks; Generative adversarial networks; Capsule networks; DL frameworks and cloud platforms; Deep learning frameworks; Cloud-based platforms for DL; Deep learning from a disaster -- Titanic survival prediction; Problem description; Configuring the programming environment; Feature engineering and input dataset preparation; Training MLP classifier ; Evaluating the MLP classifier.
متن يادداشت
Training, evaluating, and saving the trained CNN modelsNetwork construction; Scoring the model; Submission file generation; Wrapping everything up by executing the main() method; Frequently asked questions (FAQs); Summary; Answers to questions; Chapter 4: Sentiment Analysis Using Word2Vec and LSTM Network; Sentiment analysis is a challenging task; Using Word2Vec for neural word embeddings; Datasets and pre-trained model description; Large Movie Review dataset for training and testing; Folder structure of the dataset; Description of the sentiment labeled dataset; Word2Vec pre-trained model.
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
You will build full-fledged, deep learning applications with Java and different open-source libraries. Master numerical computing, deep learning, and the latest Java programming features to carry out complex advanced tasks. This book is filled with best practices/tips after every project to help you optimize your deep learning models with ease.
یادداشتهای مربوط به سفارشات
منبع سفارش / آدرس اشتراک
01201872
شماره انبار
B10335
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs.
شماره استاندارد بين المللي کتاب و موسيقي
9781788997454
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Application program interfaces.
موضوع مستند نشده
Application software-- Development.
موضوع مستند نشده
Java.
موضوع مستند نشده
Machine learning.
موضوع مستند نشده
Application software-- Development.
موضوع مستند نشده
Artificial intelligence.
موضوع مستند نشده
Computers-- Intelligence (AI) & Semantics.
موضوع مستند نشده
Computers-- Natural Language Processing.
موضوع مستند نشده
Computers-- Neural Networks.
موضوع مستند نشده
Machine learning.
موضوع مستند نشده
Natural language & machine translation.
موضوع مستند نشده
Neural networks & fuzzy systems.
رده بندی ديویی
شماره
005
.
133
رده بندی کنگره
شماره رده
QA76
.
73
.
J38
نشانه اثر
.
K375
2018
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Karim, Rezaul.
مبدا اصلی
تاريخ عمليات
20200823064244.0
قواعد فهرست نويسي ( بخش توصيفي )
pn
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب اطلاعات رکورد کتابشناسی
نوع ماده
[Book]
اطلاعات دسترسی رکورد
تكميل شده
Y
