A neural network is a unit of deep learning, which itself is sub-field of machine learning. Neural network refers to a series of algorithms that mimic the way a human brain operates to understand relationships between massive amounts of datasets.
A neural network takes input data and then trains itself to recognize patterns of the data. Based on the pattern recognition, the network then predicts the output for a new set of similar data.
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The study of the human brain is quite old. However, the first step towards the neural network started in 1943. Warren McCulloch, a neurophysiologist and a mathematician, in the year 1943, wrote a paper related to how neurons might work. During that time, a simple neural network model was created using electrical circuits.
There are four major neural network layers. These includes:
Fully Connected Layer:
Fully connected layer connects each neuron in one layer to each neuron in the next layer. These types are found in several neural networks that range from standard neural network to convolutional neural networks (CNN).
The fully connected layer forms a vital component of CNNs which can be proved beneficial in recognizing and classifying images for computer vision.
A Convolution Layer is an essential type of layer in a CNN and is used for detecting features in images. In this process, the convolution layer uses a filter through which it scans an image, a few pixels at a time. It then creates a feature map that predicts the class of each feature.
Convolution Layer is used for analyzing imagery for recognizing an image and classification.
A Deconvolution Layer is a transposed convolution method that unsamples data to high resolution in an effective way. It comprises of image data or feature maps that are formed from a convolution layer or other types of data.
Recurrent Layer has looping capacity. Its input comprises data for analysis plus output from the earlier calculation done by that layer. Recurrent layers are the base of recurrent neural network (RNN) that provide them with memory while being recursive in nature, RNN is beneficial for cases related to sequential data such as natural language and time series.
Just like humans can solve any particular problem, neural networks also have human-like ability to solve a problem. Below are some of the features of neural networks.
Below are some of the areas where we can see the application of neural network.
Speech is a way through which one communicates to others. Hence, for communication with machines, there is a need for a language that the computer or a machine can understand. These languages are quite sophisticated and are difficult to learn and use.
In present times, significant efforts have been made on this front, however, still there some issues with these systems as they are facing problems of limited vocabulary or grammar plus the challenges concerning retaining the system for different speakers in different conditions.
Artificial neural network (ANN) has played an essential role in speech recognition. Multilayer networks, multilayer networks with recurrent connections and Kohonen self-organizing feature map are some ANNs used for this purpose.
ANN is also used in the fields of Pattern Recognition. Some of the ANNs that is used for character recognition includes multilayer neural networks such as Backpropagation neural networks and neo-cognition.
Many neural networks are being developed to automatically find out handwritten character, which could be either letter or digits.
Signature of an individual plays a vital role in checking the authenticity of the user for any critical transaction or deal.
For this, the first method is to extract the feature of the signature. In the next step, the neural networks are being trained using the feature sets of the signature via an efficient algorithm. Once this gets accomplished, then the system is ready to classify the signature that is original to the one which is forged.
This can be considered as a biometric method that can identify a particular face. In the first place, the image is pre-processed and then the dimension is being reduced. In the last stage, it must be classified based on the neural network training algorithm.
What is the Dark Web? The dark web is one such portion of the World Wide Web which is not accessible by regular search engines. The dark web is considered a hotbed for criminal activities, and it is much more than that. Various websites exist on an encrypted network inside the dark web. Standard web browsers and programs cannot find these websites. Once inside the dark web, different sites and pages can be accessed like one does on the web. Scientists believe that the internet we see is only 4% of the entire ocean of the web, meaning the 96% consists of the "Deep and Dark Web". The user interface used in the dark web is usually internet-based, but it utilises special software which is not part of the standard ones. There are dozens of web browsers to surf the internet, but they all work in the same way. These standard browsers use ports and protocols to request, transfer and view data on the Internet. The website you access may look familiar, but as you enter, it may be illegal or something familiar but otherwise not monitored by anyone else. Therefore, the deep web and the dark web are famous for being anonymous. Also read: Cyber Espionage Campaign: Strings that tie China, Australia and the US How to access dark web browser? In order to access a few areas which are restricted, the user may need a password and a process to follow. A special software called TOR (The Onion Router) or the Freenet has these non-standard connections. These browsers are unlike standard internet browsers and have a process to access. They allow the users to browse around the dark web and are focused on keeping the user identity anonymous. If hacked or accessed, the regular web browser can easily provide user information such as who the user is and whereabouts. Though the dark web is providing 100% anonymity, federal agencies have been successful in tracking down criminal activities on the dark web. It is often said that the person you are talking to on the dark web could either be an FBI agent or a criminal. Image: Kalkine What happens inside the world of the dark web? The dark web is famous for allowing sinister activities, but many users go on the dark web to access information which otherwise may not be accessible on standard internet. Such as users from extremely oppressive governments who cut access to the world for their citizens. Unfortunately, such confidential environments also provide open platforms to criminals, terrorists and other such individuals involved in illegal activities. Hence, experts advise users to not access the dark web even out of curiosity as it is a lawless environment. There have been many incidents where innocent, curious users were trapped and forced to get involved in criminal activities or their digital devices hacked and compromised without their knowledge. A study conducted by a University of Surrey researcher Dr Michael McGuires in 2019, Into the Web of Profit, shows that the dark web has become worse in recent times. Since 2016 of all the listings on the dark web suggested, 60% could harm companies. Everything illegal and criminal can be found on the dark web, it also has other legitimate options such as chess clubs or book clubs, but because of the anonymity, the user will not know whom he/she is interacting with. Inside the dark web, anonymity and lawless nature make the crimes which exist otherwise in our society hard to trace. The payment procedure inside the dark web is also different from the World Wide Web. Most often, Bitcoin and Monero cryptocurrency are used for the transactions. RELATED READ: Knock Knock! Cybercriminal at Your Doorstep What’s the difference between the deep web and dark web? The dark web is part of the entire deep web and is hidden from regular browsing access. Most people confuse the deep web and the dark web as one entity. It is not. The deep web content includes anything hidden and restricted behind the security wall such as content which otherwise requires paywall or sign-in or blocked by the author. Content which cannot be easily accessible on regular internet such as medical records, membership websites, paid content are available on the deep web; hence it is also called Invisible Web. No one really knows the total size of the internet, but the experts believe that the standard World Wide Web consists of only 4% internet, the deep web consists of 90% and dark web consists of 6% of the entire internet. ALSO READ: Technology has changed the way we work amid the COVID-19 crisis: A look at in-demand technologies Image: Kalkine Also read: It happens again, NZX being bullied by Cyber-attackers- Down for the fourth day What kind of risk companies face due to the dark web? The Into the Web of Profit report listed below threats various organisations around the world are facing, especially the ones who have weak or insufficient cybersecurity measures. Malware attacks Distributed denial of service (DDoS) attacks Botnets Trojan, keyloggers, exploits Espionage Credentials access Phishing Refunds Customer data Operational data Financial data Intellectual property/ trade secrets Also read: Cybersecurity and the Requirement of a Resilient Environment in Australia Are there advantages and disadvantages to the dark web? The dark web provides complete anonymity, the users get complete privacy to perform any activity, be it illegal or legal. Many countries in the world still have authoritarian regimes offering no civil rights to their people. To such oppressed lot, the dark web provides an opportunity to access news, information, data and also express their views. The dark web is also a perfect place for law agencies to map criminal activities while being undercover. It is also easy to commit gruesome crimes through the dark web as it is complicated and lawless. Criminals can easily use the dark web to compromise someone's privacy, steal data or private information or even hire someone to commit murder. Do internet users need to be concerned about the dark web? The simple answer is no unless the user is using the dark web. Study says that most young people visit the dark web out of curiosity. They do not want to indulge in any criminal activity but want to see how the hidden and secret world of the dark web operates. And that is where the possibility of the electronic device IP address getting hacked by other criminals to perform their criminal activities lies. The earliest use of darknet dates back to the year 2000. Freenet was created at the University of Edinburgh based on a student research paper. Ian Clark wrote the paper in 1999 on the possibility of such an encrypted internet base. Freenet was created to oppose censorship and provide a platform for free speech. The most powerful dark web is TOR, and it was created by the United States government to have a secure encrypted communication in case of emergency and complete disaster. Even today, many law agencies are secretly active inside the world of the dark web to gain access in the criminal world and stay one step ahead.
What is Data Mining? Data mining is a process that facilitates the extraction of relevant information from a vast dataset. The process helps to discover a new, accurate and useful pattern in the data to derive helpful pattern in data and relevant information from the dataset for organization or individual who requires it. Key Features of data mining include: Based on the trend and behaviour analysis, data mining helps to predict pattern automatically. Predicts the possible outcome. Helps to create decision-oriented information. Focuses on large datasets and databases for analysis. Clustering based on findings and a visually documented group of facts that were earlier hidden. How does data mining work? The first step of the data mining process includes the collection of data and loading it into the data warehouse. In the next step, the data is stored and managed on cloud or in-house servers. Business analyst, data miners, IT professionals or the management team then extracts these data from the sources and accordingly access and determine the way they want to organize the data. The application software performs data sorting based on user’s result. In the last step, the user presents the data in the presentable format, which could be in the form of a graph or table. Image Source: © Kalkine Group 2020 What is the process of data mining? Multiple processes are involved in the implementation of data mining before mining happens. These processes include: Business Research: Before we begin the process of data mining, we must have a complete understanding of the business problem, business objectives, the resources available plus the existing scenario to meet these requirements. Having a fair knowledge of these topics would help to create a detailed data mining plan that meets the goals set up by the business. Data Quality Checks: Once we have all the data collected, we must check the data so that there are no blockages in the data integration process. The quality assurance helps to detect any core irregularities in the data like missing data interpolation. Data Cleaning: A vital process, data cleaning costumes a considerable amount of time in the selection, formatting, and anonymization of data. Data Transformation: Once data cleaning completes, the next process involves data transformation. It comprises of five stages comprising, data smoothing, data summary, data generalization, data normalization and data attribute construction. Data Modelling: In this process, several mathematical models are implemented in the dataset. What are the techniques of data mining? Association: Association (or the relation technique) is the most used data mining technique. In this technique, the transaction and the relationship between the items are used to discover a pattern. Association is used for market basket analysis which is done to identify all those products which customer buy together. An example of this is a department store, where we find those goods close to each other, which the customers generally buy together, like bread, butter, jam, eggs. Clustering: Clustering technique involves the creation of a meaningful object with common characteristics. An example of this is the placement of books in the library in a way that a similar category of books is there on the same shelf. Classification: As the name suggests, the classification technique helps the user to classify and variable in the dataset into pre-defined groups and classes. It uses linear programming, statistics, decision tree and artificial neural networks. Through the classification technique, we can develop software that can be modelled so that data can be classified into different classes. Prediction: Prediction techniques help to identify the dependent and the independent variables. Based on the past sales data, a business can use this technique to identify how the business would do in the future. It can help the user to determine whether the business would make a profit or not. Sequential Pattern: In this technique, the transaction data is used and though this data, the user identifies similar trends, pattern, and events over a period. An example is the historical sales data which a department store pulls out to identify the items in the store which customer purchases together at different times of the year. Applications of data mining Data mining techniques find their applications across a broad range of industries. Some of the applications are listed below: Healthcare Education Customer Relationship Management Manufacturing Market Basket Analysis Finance and Banking Insurance Fraud Detection Monitoring Pattern Classification Data Mining Tools Data mining aims to find out the hidden, valid and all possible patterns in a large dataset. In this process, there are several tools available in the market that helps in data mining. Below is a list of ten of the most widely used data mining tools: SAS Data mining Teradata R-Programing Board Dundas Inetsoft H3O Qlik RapidMiner Oracle BI
An eavesdropping attack or snooping attack is defined as an intrusion to steal the information transmitted over a network by various devices such as smartphones, computers or any device, which transmit over a network via taking advantage of unsecured network communications. ?
What is Nasdaq? Nasdaq Stock Market is a global electronic marketplace for buying and selling securities on an automatic, transparent and speedy electronic network. It trades through a computer system rather than in a physical trading floor for the traders to trade directly between them. It is an American stock exchange located in the Financial District of Lower Manhattan in New York City. NASDAQ is owned by the company Nasdaq. Inc. and ranked second on the list of stock exchanges as per market capitalisation of shares traded. The first rank goes to the New York Stock Exchange. Nasdaq-National Association of Securities Dealers Automated Quotations, was founded in 1971 by the National Association of Securities Dealers (NASD) to avoid inefficient trading and delays. Nasdaq. Inc. company also owns the Nasdaq Nordic stock market network in addition to other exchanges. The exchange has more than 3,100 companies listed. They are the highest trade volume companies in the US market, valued more than US$14 trillion in total. Good read: NASDAQ surged up above 10,000 – Tech stocks setting a new benchmark What is Nasdaq known for? Nasdaq currently is the largest electronic stock market, and it is most well-known for its high-tech stocks. But it also has a variety of companies listed such as capital goods, healthcare, consumer durables and nondurables, energy, public utilities, finance and transportation. Nasdaq boasts of having some of the largest blue-chip companies in the world and attracts high growth-oriented companies. Its stocks are known to be volatile than those listed on other exchanges. Apart from listed stocks, Nasdaq also trades in over the counter (OTC) stocks. The ticker symbols for the listed companies’ stocks on the Nasdaq have four or five letters. The Nasdaq Composite index was initially termed as Nasdaq. It included all the stocks listed on Nasdaq stock market and also many stocks listed on Dow Jones Industrial Average and S&P 500 Index. The index has more than 3,000 stocks listed on it which include the world’s largest technology and biotech giants like Microsoft, Apple, Amazon, Alphabet, Facebook, Gilead Sciences, Tesla and Intel. Did you read: Blue-chip stocks: Value versus Growth in Covid-19 Era Companies have to meet certain criteria to get listed on the NASDAQ National Market. The entities have to meet financial, liquidity, and corporate governance-related requirements. Have to get registered with the Securities Exchange Commission (SEC) Have to maintain the stock price of at least US$1. Company’s value of outstanding stocks must total at least US$1.1 million. The small companies which cannot meet the criteria can get listed on NASDAQ Small Caps Market. Nasdaq changes the companies as the eligibility of the companies keeps changing. Image: Kalkine What are different Nasdaq indexes? Nasdaq uses an index to list its stocks like any other stock exchange. The index delivers stock performance snapshots. The New York Stock Exchange (NYSE) has the Dow Jones Industrial Average (DJIA) as its primary index; it tracks the stock price of 30 big companies. Nasdaq Composite and the Nasdaq 100 are two indices of Nasdaq. Nasdaq Composite measures the performance of more than 3,100 listed companies’ stocks trading daily on Nasdaq. Nasdaq 100 is a modified capitalisation-weighted index. This index has listed companies from various sectors, but the majority is from the technology industry. Depending on their market value, Nasdaq adds or removes the companies from its index Nasdaq 100. Both the NASDAQ Composite and the NASDAQ 100 indexes have listed companies from the United States as well as global companies. On the other hand, Dow Jones Industrial Average index does not include companies outside of the US. Did you read: Hanging Up Your Boots? Investment Strategies to Help you Relax and Build Wealth Brief history Nasdaq performance in the past has been groundbreaking and extraordinary. One of its highly regarded accomplishments is that Nasdaq was the first-ever stock exchange for offering electronic trading. It was the first to launch a website and stored all the records in the cloud. Interestingly, Nasdaq also sold its technology to other stock exchanges. Nasdaq invented the modern Initial Public Offering (IPO) as it listed venture-capital-backed companies. Initially, it merged with the American Stock Exchange. It formed the Nasdaq-AMEX Market Group, later on, the AMEX index was acquired by NYSE Euronext, and the entire data was integrated into NYSE. In 2007 Nasdaq acquired OMX which is a Swedish-Finnish financial company. Followed by which Nasdaq changed its name to NASDAQ OMX Group. NASDAQ OMX Group bought the Boston Stock Exchange and also the Philadelphia Stock Exchange which was the oldest stock exchange in the US. Also read: Nasdaq index’s Tech Titans kicks off with Bold Performances How to trade on Nasdaq? Though the New York Stock Exchange is the largest exchange by market capitalisation, Nasdaq is the largest by trading volume due to its electronic quote mechanism. Nasdaq is a dealer’s market where the public buys and sells stocks with the help of the market maker (a registered broker/dealer). The market maker provides the buy and sell quotes and takes the position in those stocks. NYSE works differently as the buyers and sellers can trade directly with each other, and a specialist allows the trade. On Nasdaq, the market maker owns inventory and trade stocks in his/her capacity. Good read: Why NASDAQ Composite index plunged 5%?