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TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

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Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines.

TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms.

  • Learn TensorFlow fundamentals, including how to perform basic computation
  • Build simple learning systems to understand their mathematical foundations
  • Dive into fully connected deep networks used in thousands of applications
  • Turn prototypes into high-quality models with hyperparameter optimization
  • Process images with convolutional neural networks
  • Handle natural language datasets with recurrent neural networks
  • Use reinforcement learning to solve games such as tic-tac-toe
  • Train deep networks with hardware including GPUs and tensor processing units
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Calculus Demystified : A Self Teaching Guide
Calculus Demystified : A Self Teaching Guide
LEARNING CALCULUS JUST GOT A LOT EASIER!

Here’s an innovative shortcut to gaining a more intuitive understanding of both differential and integral calculus. In Calculus Demystified an experienced teacher and author of more than 30 books puts all the math background you need inside and uses practical examples,...

Advanced Digital Signal Processing and Noise Reduction
Advanced Digital Signal Processing and Noise Reduction
Signal processing plays an increasingly central role in the development of modern telecommunication and information processing systems, with a wide range of applications in areas such as multimedia technology, audio-visual signal processing, cellular mobile communication, radar systems and financial data forecasting. The theory and application of...
Machine Vision : Theory, Algorithms, Practicalities
Machine Vision : Theory, Algorithms, Practicalities
In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists...

Fundamentals of Probability and Statistics for Engineers
Fundamentals of Probability and Statistics for Engineers
This book was written for an introductory one-semester or two-quarter course in probability and statistics for students in engineering and applied sciences. No previous knowledge of probability or statistics is presumed but a good understanding of calculus is a prerequisite for the material.

The development of this book was guided by a
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Circuit Analysis Demystified
Circuit Analysis Demystified
Here's the sure cure for CIRCUIT PARALYSIS!

Need to learn circuit analysis but experiencing some resistance in your brain waves?  No stress! Circuit Analysis Demystified will give you the jolt you need to understand this complex subject--without getting your circuits crossed.

In the first part of the...

Free Calculus: A Liberation from Concepts and Proofs
Free Calculus: A Liberation from Concepts and Proofs
Conventional calculus is too hard and too complex. Students are forced to learn too many theorems and proofs. In Free Calculus, the author suggests a direct approach to the two fundamental concepts of calculus -- differentiation and integration -- using two inequalities. Regular calculus is condensed into a single concise chapter. This makes the...
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