Tensorflow for Deep Learning ─ From Linear Regression to Reinforcement Learning
Tensorflow for Deep Learning ─ From Linear Regression to Reinforcement Learning
  • 定  價:NT$3150元
  • 優惠價: 92835
  • 可得紅利積點:85 點
  • 庫存: 無庫存,下單後進貨(採購期約45個工作天)
  • 加入購物車
  • 商品簡介
  • 作者簡介
  • Learn how to solve challenging machine learning problems with Tensorflow, Google’s revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus, this practical book shows you how to build—and when to use—deep learning architectures. You’ll learn how to design systems capable of detecting objects in images, understanding human speech, analyzing video, and predicting the properties of potential medicines.

    TensorFlow for Deep Learning teaches concepts through practical examples and builds understanding of deep learning foundations from the ground up. It’s ideal for practicing developers comfortable with designing software systems, but not necessarily with creating learning systems. This book is also useful for scientists and other professionals who are comfortable with scripting, but not necessarily with designing learning algorithms.

    • Gain in-depth knowledge of the TensorFlow API and primitives.
    • Understand how to train and tune machine learning systems with TensorFlow on large datasets.
    • Learn how to use TensorFlow with convolutional networks, recurrent networks, LSTMs, and reinforcement learning.
  • Bharath Ramsundar received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He is currently a PhD student in computer science at Stanford University with the Pande group. His research focuses on the application of deep-learning to drug-discovery. In particular, Bharath is the lead-developer and creator of DeepChem.io, an open source package founded on TensorFlow that aims to democratize the use of deep-learning in drug-discovery. He is supported by a Hertz Fellowship, the most selective graduate fellowship in the sciences.

    Reza Bosagh Zadeh is Founder CEO at Matroid and Adjunct Professor at Stanford University. His work focuses on Machine Learning, Distributed Computing, and Discrete Applied Mathematics. Reza received his PhD in Computational Mathematics from Stanford University under the supervision of Gunnar Carlsson. His awards include a KDD Best Paper Award and the Gene Golub Outstanding Thesis Award. He has served on the Technical Advisory Boards of Microsoft and Databricks.

    As part of his research, Reza built the Machine Learning Algorithms behind Twitter's who-to-follow system, the first product to use Machine Learning at Twitter. Reza is the initial creator of the Linear Algebra Package in Apache Spark and his work has been incorporated into industrial and academic cluster computing environments. In addition to research, Reza designed and teaches two PhD-level classes at Stanford: Distributed Algorithms and Optimization (CME 323), and Discrete Mathematics and Algorithms (CME 305).


      • 青森弘前‧津輕‧十和田
      • 優惠價:251元
      • 香氛聖經:調香師的祕密配方
      • 優惠價:461元
      • 模糊的疆界:易宗唐手道創始人洪懿祥大師傳奇
      • 優惠價:330元
      • 開店創業天時˙地利˙人和招財術
      • 優惠價:223元
      • 完全網銷手冊:提升你的網路行銷即戰力
      • 優惠價:284元
      • 金牌助理(簡體書)
      • 優惠價:75元
      • 科學與歷史
      • 優惠價:403元
      • 心懷正向的信念(簡體書)
      • 優惠價:178元
      • 李善東生命清潔中心
      • 優惠價:238元
      • 我的回憶(三版)─三民叢刊284
      • 優惠價:125元