Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Applied Neural Networks with TensorFlow 2 (sách keo gáy bìa mềm )
Categories:Computers - Artificial Intelligence (AI)
Year:2021
Edition:1st ed.
Publisher:Apress
Language:english
Pages:306
Implement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations.
You’ll
start by learning what deep learning offers over other machine learning
models. Then familiarize yourself with several technologies used to
create deep learning models. While some of these technologies are
complementary, such as Pandas, Scikit-Learn, and Numpy—others are
competitors, such as PyTorch, Caffe, and Theano. This book clarifies the
positions of deep learning and Tensorflow among their peers.
You'll
then work on supervised deep learning models to gain applied experience
with the technology. A single-layer of multiple perceptrons will be
used to build a shallow neural network before turning it into a deep
neural network. After showing the structure of the ANNs, a real-life
application will be created with Tensorflow 2.0 Keras API. Next, you’ll
work on data augmentation and batch normalization methods. Then, the
Fashion MNIST dataset will be used to train a CNN. CIFAR10 and Imagenet
pre-trained models will be loaded to create already advanced CNNs.
Finally, move into theoretical applications and unsupervised learning
with auto-encoders and reinforcement learning with tf-agent models. With
this book, you’ll delve into applied deep learning practical functions
and build a wealth of knowledge about how to use TensorFlow effectively.
What You'll Learn
Compare competing technologies and see why TensorFlow is more popular
Generate text, image, or sound with GANs
Predict the rating or preference a user will give to an item
Sequence data with recurrent neural networks
Who This Book Is For
Data scientists and programmers new to the fields of deep learning and machine learning APIs.
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