Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Machine Learning with TensorFlow (sách keo gáy bìa mềm)
Thể loại:Computers - Computer Science
Năm:2020
In lần thứ:2
Ngôn ngữ:english
Trang: 454
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
About the reader
Requires
intermediate Python skills and knowledge of general algebraic concepts
like vectors and matrices. Examples use the super-stable 1.15.x branch
of TensorFlow and TensorFlow 2.x.
About the author
Chris Mattmann
is the Division Manager of the Artificial Intelligence, Analytics, and
Innovation Organization at NASA Jet Propulsion Lab. The first edition of
this book was written by Nishant Shukla with Kenneth Fricklas.
