good intro into MLOps - I'm not new to it, but some aspects were well formulatedgood intro into MLOps - I'm not new to it, but some aspects were well formulated...more
Good overview of ML-based approaches to improve search quality. One big selling points is that book was updated to include latest developments in areaGood overview of ML-based approaches to improve search quality. One big selling points is that book was updated to include latest developments in area of LLMs, and how they could be applied to search-related stuff.
P.S. I was technical proofreader for this book, and read the prerelease version, not final one....more
Very good practical introduction into deep learning based on the Keras. Author explains all major architectures of neural network(maybe close to 9/10)
Very good practical introduction into deep learning based on the Keras. Author explains all major architectures of neural networks without digging into mathematics, on practical examples that are easy to adapt to your own tasks. ...more
Very good survey on the topic of multilabel classification. If you need more details on each of the described algorithms, approaches, then you need toVery good survey on the topic of multilabel classification. If you need more details on each of the described algorithms, approaches, then you need to have access to the referred papers.
P.S. So the size my reading queue is really increased instead of decreasing ;-)...more
short, quite good book (freely available from O'Reilly) on how to evaluate quality of the machine learning models...short, quite good book (freely available from O'Reilly) on how to evaluate quality of the machine learning models......more
Great book on Elasticsearch. Besides introduction of main Elasticsearch's features, it covers also many relevant areas, including Geo-search, selectioGreat book on Elasticsearch. Besides introduction of main Elasticsearch's features, it covers also many relevant areas, including Geo-search, selection/customization of analyzers, etc. Chapter about putting ES into production, with DO/DON'T DO list could be very helpful for many people who starting to use ES....more
Disclaimer: I got this book from Packt Publishing, but I planned to read it anyway...
Real rating is between 3 & 4 - 3 mostly for the not so good formaDisclaimer: I got this book from Packt Publishing, but I planned to read it anyway...
Real rating is between 3 & 4 - 3 mostly for the not so good formatting - I'd read the mobi version of the book, and expected that referenced external resources/papers will be hyperlinked as in the most of the books (from Manning & O'Reilly, for example), providing the easy way to access them.
The book starts by covering basic matrix operations using the core.matrix, and after that describes most popular ML tasks/algorithms - linear regression, data categorization (providing naive bayes implementation), neural networks, SVMs, clustering & anomaly detection. It also shows how to perform cross-validation of the models using the spam classifier as an example.
The book is easy to follow - you need to know relatively small subset of the Clojure (but you need to know it already!), and basic understanding of the ML tasks. In some cases, book provides complete implementations using the Incanter, core.matrix & built-in Clojure functions, and in some cases (neural networks, SVMs, etc.) it uses wrappers for existing libraries like Weka, liblinear, etc. Code style sometime not consistent, and could be improved, but in general is ok.
I could recommend this book if you're interested in implementing ML tasks in Clojure - you can get some pieces of code from it. But don't expect that you get deep understanding of the theory behind ML - you need to take some other books....more
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