Computer Network Topologies The term topology refers to the way a network is laid out, either physically or logically. The connection of two or more devices forms a link and two or more links forms a topology. The topology of a network is the geometric   representation of the relationship of all the links and linking devices to one another. Basically, there are five topologies – mesh, star, tree, bus, and ring. 1)       Mesh:- Every devices has a dedicated point-to-point link to each other devices in a mesh topology. Therefore a fully connected mesh network has n(n-1)/2 physical channels to link n devices.           Mesh topology has several advantages:- a)       The use of dedicated links guarantees that each connection can carry its own data load,   therefore minimizing the traffic problems which can take place if links much be shared by multiple devices. b)       It is robust. It does not incapacitate the entire system when one link damages. c)        It enforces priv

Advantages of machine learning The advantages of machine learning are as follows-        Accurate       Automated       Fast       Customizable        Scalable   1)       Accurate: - Machine learning uses data to discover the optimal decision making engine for your problem. As you collect more data, the accuracy can increase automatically. 2)        Automated: - as answers are validated or discarded, the machine learning model can learn new patterns automatically. This allows users to embed machine learning directly into an automated workflow. 3)        Fast: - Machine learning can generate answers in a matter of milliseconds as new data streams in, allowing systems to react in real time. 4)       Customizable: - Many data-driven problems can be addressed with machine learning. Machine learning models are custom built from your own data, and can be configured to optimize whatever metric drives your business. 5)       Scalable:- As your business grows, machine learn

  Application of computer network   Some of the network applications in different fields are the following-     Marketing and Sales      Manufacturing     Financial Services     Teleconferencing     Cable Television     Information Services     Electronic Messaging     Electronic Data Interchange (EDI)    Directory Services   Cellular Telephone   1.         Marketing and Sales:-   Computer networks are widely used in both marketing and sales firms. These are used by the  marketing professionals to collect, exchange, and analyzes data relating to customer  requirements and product development cycles.         2.        Manufacturing:-     Now a days, computer networks are used in several aspects of manufacturing, including the  manufacturing process itself. 3.        Financial Services:-  In present, financial services are completely dependent on computer and networks. Main applications are credit history searches, foreign exchange and investment servic

  Computer Networking goals with its classification The most important goals of computer networks are- 1)       Reliability Goals 2)       Performance Goals 3)       Security Goals 4)       Network Cast   1)        Reliability Goals:-  Network reliability can be measured by the networks robustness in a catastrophe, failure frequency    and average down time of network. These are described as follows- a)       Catastrophe b)       Failure Frequency c)        Average Down Time   a)        Catastrophe:-  Network should be protected from catastrophe events like theft or earthquake. One protection  of network against these is a reliable system to backup network software.           b)       Failure Frequency:-    A network which fails rarely is good for a user but a network which fails oftently is of little  value to a user.                 c)        Average Down Time:-   How long does it take to restore service is called down time. A network with less value of

https://drive.google.com/file/d/1h3yY8tN8Jh7xkwO_qWplvvqbbwckU-Ch/view?usp=drivesdk   In the above link you can check all the information about framing in detail.  Framing To service the network layer, data link layer uses the service provided to it by the physical layer. Physical layer accepts the raw bit stream and delivers it to destination. This bit stream may contain error i.e., number of bits received may not be equal to number of bits transmitted. various simple methods used for framing are- a)          Character count b)       Starting and ending character, with character stuffing c)        Starting and ending flags, with bit stuffing. The different types of framing protocols are as follows:- 1)       Character-oriented Protocols 2)       Bit-oriented protocols 1)        Character-oriented Protocols The format of a frame in a character-oriented protocol . Data to be carried are 8-bit characters from a coding system like ASCII in a character-oriented protocol.  

  Regression Regression models are used to predict a continuous value. Predicting prices of a house given the features of house like size, price etc. is one   of the common examples of regression. It is a supervised technique. Types of Regression: -   Simple Linear Regression  Polynomial regression Support Vector Regression   Decision Tree Regression   Random Forest Regression 1.         Simple Linear Regression:-   This   si one of most common and interesting type of regression technique. Here we predict a target variable Y based on the input variable X. A linear relationship should exist between target variable and predictor and so comes the name linear regression. 2.         Polynomial Regression: -   In polynomial regression, we transform the original features into polynomial features of a given degree and then apply linear regression on it. 3.         Support Vector Regression :-   In SVR, we identify a hyper plane with maximum margin such that maximum numbers of data po

  Machine Learning Machine learning is a tool for turning information into knowledge.   Machine learning techniques are used to automatically find the valuable underlying patterns within complex data that   we would otherwise struggle to discover. The hidden patterns and knowledge about   a   problem   can be used to predict future events and perform all kinds of complex decision making. Tom Mitchell gave a “well-posed” mathematical   and relational definition that   “A computer program its performance on T, as measured by   P, improves with experience   E”. Types of Machine Learning:- 1)       Supervised   Learning: -   Supervised Learning is the one, where you can consider the learning is guided by a teacher. We have a dataset which acts as a teacher and its role is to train the model or the machine. Once the model gets trained it can start making a prediction or decision when new data is given to it. 2)        Unsupervised Learning:-   The model learns through observation