bookmarket (ibook)

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This project was a part of Spikeway Technologies AI Lab(SAIL) and discusses the classification of books based only on title, without prior knowledge or context of author and origin. The total number of genres for the books to be classified into is 32.

This blog mainly tells the story of the Machine Learning life-cycle, starting with a business problem to finding the solution and deploying the model. This helps beginners and mid-level practitioners to connect the dots and build an end-to-end ML model. Here are the steps involved in an ML model lifecycle.

We are going to work on a specific sub-task of NLP called text classification, this is the process of recognizing a pattern in a text and assign it a label.

Digitization has changed the way we process and analyze information. There is an exponential increase in online availability of information. From web pages to emails, science journals, e-books, learning content, news and social media are all full of textual data. The idea is to create, analyze and report information fast.

In this post, we'll implement several machine learning algorithms in Python using Scikit-learn, the most popular machine learning tool for Python. Using a simple dataset for the task of training a classifier to distinguish between different types of fruits.

When smart contracts are deployed into the Ethereum blockchain, they are immutable and therefore, no upgradable. By re-architecturing the code into different contracts, it is possible to allow logic upgrades while keeping the storage the same. In fact, upgradable smarts contracts are becoming popular and Jack Tanner had a good article explaining all the techniques used.

In my tenure as a solution architect in financial services working for a global consulting firm, I have often questioned the best way to practice enterprise architecture. A common challenge that many architecture consultants face is that most client firms insist on using their proprietary enterprise architecture content.

Reader Analytics by Jellybooks allows book publishers to collect data on how their customers read books across third party reading apps and devices. This ebooks analytics tools for book reading uses many of the same technical principles used in Google Analytics for web pages.