Informasi Umum

Kode

24.21.491

Klasifikasi

519.5 - Statistical mathematics, parametric and nonparametric methods

Jenis

Buku - Elektronik (E-Book)

Subjek

Statistical

No. Rak

10b

Informasi Lainnya

Abstraksi

Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library. Written by NASA JPL Deputy CTO and Principal Data Scientist Chris Mattmann, all examples are accompanied by downloadable Jupyter Notebooks for a hands-on experience coding TensorFlow with Python. New and revised content expands coverage of core machine learning algorithms, and advancements in neural networks such as VGG-Face facial identification classifiers and deep speech classifiers.

About the Technology Supercharge your data analysis with machine learning! ML algorithms automatically improve as they process data, so results get better over time. You don’t have to be a mathematician to use ML: Tools like Google’s TensorFlow library help with complex calculations so you can focus on getting the answers you need.

About the book Machine Learning with TensorFlow, Second Edition is a fully revised guide to building machine learning models using Python and TensorFlow. You’ll apply core ML concepts to real-world challenges, such as sentiment analysis, text classification, and image recognition. Hands-on examples illustrate neural network techniques for deep speech processing, facial identification, and auto-encoding with CIFAR-10.

What's inside • Machine Learning with TensorFlow • Choosing the best ML approaches • Visualizing algorithms with TensorBoard • Sharing results with collaborators • Running models in Docker

Koleksi & Sirkulasi

Tersedia 1 dari total 1 Koleksi

Pengarang

Nama	James U. Gleaton, David Han,
Jenis	Perorangan
Penyunting
Penerjemah

Penerbit

Nama	Springer
Kota	New York
Tahun	2022

Sirkulasi

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

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