Applied Neural Networks with TensorFlow 2: API Oriented Deep Learning with Python
Orhan Gazi Yalç?n

Informasi Umum

Kode

22.21.503

Klasifikasi

006.32 - Neural networks, perceptrons, connectionism, neural computers

Jenis

Buku - Elektronik (E-Book)

Subjek

Neural Networks

No. Rak

4

Dilihat

6 kali

Informasi Lainnya

Abstraksi

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.

Koleksi & Sirkulasi

Tersedia 1 dari total 1 Koleksi

Pengarang

Nama	Orhan Gazi Yalç?n
Jenis	Perorangan
Penyunting
Penerjemah

Penerbit

Nama	Apress Media
Kota	New York
Tahun	2021

Sirkulasi

Harga sewa	IDR 0,00
Denda harian	IDR 1.000,00
Jenis	Non-Sirkulasi

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