Answer:
by using forms
Explanation:
Most of the database users perform the data searches by using the forms. A form can be used to enter, edit and display the data from the data source. Its a user interface in fact that fetches the data from the database. Reports have used the display the data for a certain type of user, and the viewing table does not look feasible to search from a very large database, and the databases are usually large. No calculation is required for searching the data, and we only need to write queries in the right syntax. Hence, here the correct option is by using forms.
Answer:
Advantages of both circuit switched networks and TDM are given below:
Explanation:
Advantages of circuit switched network over packet switched network:
- Circuit switched network has the advantage of being physically connected and having a dedicated channel for communication between the sender and the receiver which also makes it more reliable. Packet switched networks do not have a dedicated channel hence, they are not that reliable.
- Circuit switched networks are used for voice calls because there is no timing jitter or delay in these types of networks while packet switched networks do not offer this advantage.
Advantages of TDM over FDM in a circuit switched network:
- TDM is time division multiplexing i.e. multiple information is sent in different time intervals but on the same frequency. While FDM sends information using different frequencies. So, the advantage of using TDM is that the information will be sent from the sender to the receiver using only a single frequency.
- Using TDM, bandwidth is saved because it only sends information on a single frequency unlike FDM.
- In TDM, there is low chance of interference between signals since they are sent in different time intervals from the sender to the receiver. While FDM has a higher chance of interference.
Answer:
Kindly check Explanation.
Explanation:
Machine Learning refers to a concept of teaching or empowering systems with the ability to learn without explicit programming.
Supervised machine learning refers to a Machine learning concept whereby the system is provided with both features and label or target data to learn from. The target or label refers to the actual prediction which is provided alongside the learning features. This means that the output, target or label of the features used in training is provided to the system. this is where the word supervised comes in, the target or label provided during training or teaching the system ensures that the system can evaluate the correctness of what is she's being taught. The actual prediction provided ensures that the predictions made by the system can be monitored and accuracy evaluated.
Hence the main difference between supervised and unsupervised machine learning is the fact that one is provided with label or target data( supervised learning) and unsupervised learning isn't provided with target data, hence, it finds pattern in the data on it's own.
A to B mapping or input to output refers to the feature to target mapping.
Where A or input represents the feature parameters and B or output means the target or label parameter.
