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Convolutional Neural Networks Guide to Algorithms, Artificial Neurons, and Deep Learning: Introduction to Feedforward Neural Networks
- Artificial Intelligence, Book 2
- Narrated by: Lukas Arnold
- Length: 53 mins
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Publisher's summary
The very schemata of Convolutional Neural Networks and the technology behind it was inspired by our biological human brains!
Its a known fact that computers can store exponential amounts of information on their hard-drives. But our human brains have a set capacity and just cannot compete against technology on this front. However, our biological brains can outpace a computer in some other everyday functions we take for granted.
Engineers and scientist are discovering ways to model our human brains and integrate certain aspects of it to create what we know as "neural networks". In essence, replicate the fine tuning, inner complexities and intricacies the human brain possess.
In my book, Convolutional Neural Networks Guide to Algorithms, Artificial Neurons, and Deep Learning, you will learn the following concepts:
- Fundamentals of neural networks
- Intelligent systems
- Functioning of the feed-forward neural network
- Back-propagation
- Algorithms
- And, much, much more!
You do not want to miss out on this incredible offer! Take this opportunity to learn about the next big innovation in technology and real-world applications of the next potential trillion-dollar industry (artificial intelligence) that will take the world by storm.
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Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.
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Rigorously Bayesian
- By Anonymous User on 01-25-22
By: Aubrey Clayton
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The Theory of Everything: The Quest to Explain All Reality
- By: Don Lincoln, The Great Courses
- Narrated by: Don Lincoln
- Length: 12 hrs and 21 mins
- Original Recording
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At the end of his career, Albert Einstein was pursuing a dream far more ambitious than the theory of relativity. He was trying to find an equation that explained all physical reality - a theory of everything. Experimental physicist and award-winning educator Dr. Don Lincoln takes you on this exciting journey in The Theory of Everything: The Quest to Explain All Reality. Suitable for the intellectually curious at all levels and assuming no background beyond basic high-school math, these 24 half-hour lectures cover recent developments at the forefront of particle physics and cosmology.
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Audible’s Best Science Offering, A Gem
- By MikeB on 12-08-18
By: Don Lincoln, and others
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Zombified: Real-World Lessons from Fictional Apocalypses
- By: Athena Aktipis, The Great Courses
- Narrated by: Athena Aktipis
- Length: 2 hrs and 33 mins
- Original Recording
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Athena Aktipis of Arizona State University is a self-professed apocalypse enthusiast, and as the host of the podcast Zombified, she knows the undead inside and out. With Zombified: Real-World Lessons from Fictional Apocalypses, she’s compiled her research and insights into a fascinating Audible Original that will have you thinking deeper about all those shambling, brain-hungry corpses in pop culture—not to mention our everyday lives. Drawing on years of research on zombies and zombification, these six lessons offer a fun way to explore and understand the many forces that influence us.
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Good attempt, lackluster execution
- By R. MCRACKAN on 10-14-23
By: Athena Aktipis, and others
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Welcome to the Universe
- An Astrophysical Tour
- By: Michael A. Strauss, J. Richard Gott, Neil deGrasse Tyson
- Narrated by: Michael Butler Murray
- Length: 17 hrs and 53 mins
- Unabridged
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Welcome to the Universe is a personal guided tour of the cosmos by three of today's leading astrophysicists. Inspired by the enormously popular introductory astronomy course that Neil deGrasse Tyson, Michael A. Strauss, and J. Richard Gott taught together at Princeton, this book covers it all - from planets, stars, and galaxies to black holes, wormholes, and time travel.
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All About What We Know About the Universe - ALL
- By J.B. on 02-17-17
By: Michael A. Strauss, and others
What listeners say about Convolutional Neural Networks Guide to Algorithms, Artificial Neurons, and Deep Learning: Introduction to Feedforward Neural Networks
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- imzhat
- 02-21-18
great boook
This book teach me about convolution Learning.
It guide me well in the right process.
I like reading it. The steps are easy to comprehend.
They covered machine problem and how to solve it which I find great to have better knowledge about it.
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- shibli
- 02-21-18
powerful
To learning this term Convolutional learning becomes easy with the help of this beginners appropriate guide book. These guide book teachings will assist you in understanding and learning algorithms and machine learning tools that you could use, data acquisition and data management and much more informational about this term, appreciated book
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- chota
- 02-21-18
truly amazing
Truly and amazing prologue to Machine Learning. It begins toward the start and advances through the significant subjects with clear illustrations. This is a fabulous book for the supreme fledgling. Albeit to a great degree rudimentary in content, it is extremely valuable for somebody with no background.
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- pinky
- 02-21-18
great examples
Great book. Explanation are very through and deliver exactly what is needed. Book also has a lot of visual elements to help better understand the details of the topic.Example is very good
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- H. Hampton
- 02-23-18
go for it
Excellent audiobook. It fills in many of the math steps typically left out of most used this text books in colleges
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- smith
- 02-23-18
great intelligence
This book could be a nice refresher, but mainly it seems useful to someone who is taking a signals and systems class, who is a already up to speed, who wants a little better understanding of the material then their book or professor provides.
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- Ashley H McNeely
- 02-21-18
new techniqes
I find this book instructive and informative. The tips and techniques are quite interesting.
I like it a bunch coz I learn a lot.
If you are newbie, this book is perfect for you to learn data management, model training. neural networks and even learning
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- Connie
- 02-21-18
great guide
This book is a great guide for anyone who is curious about machine learning just like me, but has no idea where to start. I imagine there are a lot of people who tried to google and got frustrated and gave up wishing someone would just give them a high-level explanation. That’s why when my sister referred this book, without hesitations, i grabbed it right away.
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- Eula Schultz
- 02-23-18
useful book
This book presents a good amount of material. It also has a good amount of solved problems for each section and usually explains what is going on. For the price I can't find anything wrong with it
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- Andrea
- 02-21-18
good start
Very helpful in understanding the basic concepts. Easy to understand language and clear examples make this book a good start point
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