{"product_id":"markov-models-introduction-to-markov-chains-hidden-markov-models-and-bayesian-networks-paperback","title":"Markov Models: Introduction to Markov Chains, Hidden Markov Models and Bayesian Networks - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eJoshua Chapmann\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eWhat is a \u003cb\u003eMEMORYLESS\u003c\/b\u003e predictive model? \u003c\/p\u003e\u003cp\u003e Markov models are a powerful predictive technique used to model stochastic systems using time-series data. They are centered around the fundamental property of \"memorylessness\", stating that the outcome of a problem depends only on the current state of the system - historical data must be ignored. \u003c\/p\u003e \u003cp\u003e This model construction may sound overly simplistic. After all, if you have historical data why not use it to develop more complete and well-informed models? Surely, it would lead to more accurate predictions.\u003c\/p\u003e \u003cp\u003eHowever, when modelling time-series data where previous results are of limited relevance, a memoryless model delivers vast performance advantages. By considering only the present state, algorithms become highly scalable, stable, fast and, above-all-else, extremely versatile. Speech recognition is a perfect example - nearly all of today's speech recognition algorthms are built using Markov Models. \u003c\/p\u003e \u003cp\u003e In this book we will explore why a \u003cb\u003eMemoryless\u003c\/b\u003e predictive model can be so advantageous to the modern tech industry. We will take a look at fundamental mathematics and high-level concepts alike, extending our understanding of the subject beyond the simple Markov Model.\u003c\/p\u003e You will learn... \u003cul\u003e \u003cli\u003eFoundations of Markov Models\u003c\/li\u003e \u003cli\u003eMarkov Chains\u003c\/li\u003e \u003cli\u003eCase Study: Google PageRank\u003c\/li\u003e \u003cli\u003eHidden Markov Models\u003c\/li\u003e \u003cli\u003eBayesian Networks\u003c\/li\u003e \u003cli\u003eInference Tasks\u003c\/li\u003e \u003c\/ul\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 106\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.25 x 9 x 6 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e October 29, 2017\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":54061172293939,"sku":"9781978304871","price":47.48,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/qxvMJbL7Zm9781978304871.webp?v=1789116625","url":"https:\/\/www.vysn.com\/en-ca\/products\/markov-models-introduction-to-markov-chains-hidden-markov-models-and-bayesian-networks-paperback","provider":"VYSN","version":"1.0","type":"link"}