Fundamentals of Deep Learning: Designing Next-Generation

Fundamentals of Deep Learning: Designing Next-Generation Artificial Intelligence Algorithms FUNDAMENTALS OF DEEP LEARNING Paperback NotRetrouvez FUNDAMENTALS OF DEEP LEARNING Paperback Jan ,BUDUMA et des millions de livres en stock surAchetez neuf ou d occasion Fundamentals of Deep Learning Designing Next GenerationDeep Learning Fundamentals of Deep Learning for Beginners Artificial Intelligence BookEnglish Edition Rudolph Russell Format Kindle , Suivant Commentaires client , surtoiles , sur Evaluations clientstoiles % % %toiles % % %toiles % % %toiles % % %toile % % % Comment est ce quprocde Fundamentals of Deep Learning Buduma, NikhilNotRetrouvez Fundamentals of Deep Learning et des millions de livres en stock surAchetez neuf ou d occasion Fundamentals of Deep Learning and Computer Vision AAchetez et tlchargez ebook Fundamentals of Deep Learning and Computer Vision A Complete Guide to become an Expert in Deep Learning and Computer Vision English Edition Boutique Kindle Artificial IntelligenceServeur de Pages Professionnelles Individuelles Serveur de Pages Professionnelles Individuelles Fundamentals of Deep Learning Analytics Vidhya Key takeaways from Fundamentals of Deep Learning Course These deep learning algorithms are powered by techniques like Convolutional Neural Networks CNN , Recurrent Neural Networks RNN , Long Short Term Memory LSTM , etc I am finished with the number of chapters that have been released so far There have been three in total The material is a little rough but it is an early release One should have some basic understanding of statistics and probability before attempting to digest the material Looking forward to the additional chapters. When in school, we often used a term to label things that were hard to comprehend OHT or Over Head Transmission Essentially, concepts that the brain failed to catch This book felt the same at many levels It was great once again encounter calculus, vectors, transforms and matrices, long after school and college days I can t say I understood them with the same rigor as when in school though Reading this book didn t help me understand Neural Networks all that much as it made me familiar wi When in school, we often used a term to label things that were hard to comprehend OHT or Over Head Transmission Essentially, concepts that the brain failed to catch This book felt the same at many levels It was great once again encounter calculus, vectors, transforms and matrices, long after school and college days I can t say I understood them with the same rigor as when in school though Reading this book didn t help me understand Neural Networks all that much as it made me familiar with the associated terminology gradient descent, soft max output layer, feed forward, Sigmoid Tanh ReLU, Training Validation Test data sets, overfitting, L1 L2 regularization Max norm constraints Dropout, tensor Flow, Stochastic Gradient Descent, local minima, learning rate adaptation, Convolution networks, Principal Component Analysis, Word2Vec, LSTM, SkipGram, seq2seq, Beam search, vanishing gradients, RNN, NTM, Differential Neural Computers, Markov Decision Process, Explore vs Exploit, Deep Q Network, Deep Recurrent Q Networks DRQN , Asynchronous Advantage Actor Critic Agent A3C , UNsupervised REinforcement and Auxiliary Learning UNREAL one gets the idea.I found the book was rich on concepts and ideas but not as lucid on explanations I had to refer to the web several times to understand what author was trying to say and found some of the explanations on the web easier to comprehend On the social side, this book makes it quite obvious why the divide between the haves and the have nots in our society continues to deepen and widen irreparably and at great pace Machine Learning, which is increasingly becoming the bedrock of technical solutions and business strategy, is a very complex topic Unlike the complexities of the Industrial Age, much of which could be overcome with on the job training, the new technical concepts require rigorous technical education in advanced computational, statistical, and mathematical topics This education is not an easily available or economically viable option for majority of the worlds population In addition, even if we take into account that not everyone has to learn these subjects one still has to grapple with the envy generated when regular folks have to live in the shadow of the ensuing monetary success of the masters of these sciences However, not all is lost This technology may not be within reach of all but its outcomes have the ability to influence all lives just as much These outcomes are of human choosing Whether these will deepen the divide by trying to sellto those who can buy or bridge the gaps in human condition by creating solutions to knowledge, goods and service distribution, is a choice we as a society need to make Our world, is our responsibility Its one of the few books, that combines practical and theoretical information in a very balanced way The first half of the book for me was very easy to follow But I need to add, before the book, I have finished Andrew Ng s 16 week Machine Learning course, read a couple other books on Data Science and did some basic math coding on the various ML AI areas Somehow, up to Convolutional Neural Networks %50 of the book , there is a very good overview of what Gradient Descent is and how to impleme Its one of the few books, that combines practical and theoretical information in a very balanced way The first half of the book for me was very easy to follow But I need to add, before the book, I have finished Andrew Ng s 16 week Machine Learning course, read a couple other books on Data Science and did some basic mathcoding on the various ML AI areas Somehow, up to Convolutional Neural Networks %50 of the book , there is a very good overview of what Gradient Descent is and how to implement and use it After CNN things getserious and it moves onto relatively newly discovered and production level state of the art models like the basic model powering Google Translate The last chapter is about Deep Reinforcement Learning Deep Minds astonishing model for all Atari games and ends with very recent topics like Async Advantage Actor Critic Agents and UNREAL I would be happier if I would seecomputer vision related models and problems instead of sentiment and sequence analysis but its completely a personal preference I strongly recommend this book if you have interest in Deep Learning If you expect code example, you would be disappointed This book is very good at covering fundamentals, which I like I suggest this book as a supplement with other deep learning book.

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