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Book Categories |
| Foreword | ||
| 1 | Introduction | 1 |
| 2 | Mathematical background for neural computing | 5 |
| 3 | Managing a neural computing project | 37 |
| 4 | Identifying applications and assessing their feasibility | 49 |
| 5 | Neural computing hardware and software | 59 |
| 6 | Collecting and preparing data | 67 |
| 7 | Design, training and testing of the prototype | 77 |
| 8 | The case studies | 99 |
| 9 | More advanced topics | 121 |
| App. A | The error back-propagation algorithm for weight updates in an MLP | 129 |
| App. B | Use of Bayes' theorem to compensate for different prior probabilities | 131 |
| References | 133 | |
| Index | 137 |
| Price | Condition | Delivery | Seller | Action |
| $113.28 | Digital |
| WonderClub |
Derek Elsey
reviewed Guide to Neural Computing Applications on October 28, 2018
Guide to Neural Computing Applications
Fascinating read but quite outdated
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Add Guide to Neural Computing Applications, Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of dat, Guide to Neural Computing Applications to the inventory that you are selling on WonderClubX
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Add Guide to Neural Computing Applications, Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of dat, Guide to Neural Computing Applications to your collection on WonderClub |