Data Structures and Algorithms and others

Smart Contract Due to the cost-saving benefits that smart contracts can bring to the financial services industry by reducing the cost of transactions and simplifying complex contracts, rigorous research is being carried out by various commercial and academic institutions to formalize and make the implementation of smart contracts easy. History Smart contracts were first theorized by Nick Szabo in the late 1990s in an article named Formalizing and Securing Relationships on Public Networks. As described by Szabo “ A smart contract is an electronic transaction protocol that executes the terms of a contract. The general objectives are to satisfy common contractual conditions (such as payment terms, liens, confidentiality, and even enforcement), minimize exceptions both malicious and accidental, and minimize the need for trusted intermediaries. Related economic goals include lowering fraud loss, arbitrators and enforcement costs, and other transaction costs. ” The original article written b...

Book By TERRENCE J. SEJNOWSKI Sharks and Rays(Which include skates) are able to sense very weak electrical fields; indeed, they can detect the signal from a 1.5-volt battery clear across Atlantic Ocean. With this 6th sense, skates can navigate by the weak electrical signals from their motion through the earth's magnetic field, which generates microvolt signals in their electroreceptors. Hermann von Helmholtz was a nineteenth-century physicist and physician who developed a mathematical theory and an experimental approach to vision that forms the basis for our current understanding of visual perception. Vision is our most acute and also our most studied sense. With two frontal eyes, we have exquisite binocular depth perception, and half of our cortex is visual. In one tenth of a second, ten billion neurons in our visual cortex working together in parallel can identify a cup in a cluttered scene, even though we may have never seen that particular cup before and even when it m...

Why Machine Learning & Security? Spam As soon as academics and scientists had hooked enough computers together via the internet to create a communications network that provided value, other people realized that this medium of free transmission and broad distribution was a perfect way to advertise sketchy products, steal account credentials, and spread computer viruses ClicK Machine Learning Machine Learning is not invented by the spam fighters, but it was quickly adopted by statistically inclined technologies who saw its potential in dealing with a constantly evolving source of abuse. Email providers and Internet Service Providers (ISPs) have access to wealth to email content, metadata, and user behavior. Using email data, content based models can be built to create a generalizable approach to recognize spam. Metadata and entity reputation can be extracted from emails to predict the likelihood that an email is spam without even looking at its content. By instantiating a...

Designing Data Intensive Application A data-intensive application is typically built from standard building blocks that provide commonly needed functionality. For Example, many applications need to: Store data so that they, or another application, can find it again later(databases). Remember the result of an expensive operation, to speed up reads (caches) Allow users to search data by keyword or filter it in various ways (search indexes) Send a message to another process, to be handled asynchronously (stream processing) Periodically crunch a large amount of accumulated data (batch processing) Data Systems We typically think of databases, queues, caches etc. as being very different categories of tools. Although a database and a message queue have some superficial similarity -- both store data for some time-they have very different access patterns, which means different performance characteristics, and thus very different implementations. For example, there are d...