Answer:
Option 3 is the correct answer for the above question.
Explanation:
- A tarball is a software which is used to encrypt the other software or hide the other software and make it small. It again makes the original software program from the encrypted ones.
- It is used to make the file sort and can use for the transfer which takes some amount of memory.
- The above question asked about that technology which is used to make encrypted software from the original software and use it with the help of some script. Then the answer is tarball which is referred to from option 3. Hence Option 3 is the correct answer for the above question while the other is not because--
- Option 1 states about the package manager which is used to manage the library only.
- Option 2 states about the DBMS which is used to manage the database.
- Option 4 states about the router which is used for the internet.
<span>The schema will have to accommodate to make the person more easily able to perform the new task. Accommodation allows the new information to be made a part of a schema without changing the overall concepts in the schema. The schema itself stays unchanged for the most part, but the new information is more of a "tweak" to the schema than a full-on update.</span>
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.
