Answer:
Im twelve but i know something about economics. The more homeless the more free coupons the government give out which the middle and high class pay for. The more people the higher the taxes and inflation causing the middle class to shrink making only rich and poor people. The U.S. then will have more homeless.
Explanation: Larg bwain finking
Answer:
The attached files contain the realization of a D flip-flop from an RS flip-flop. It also contains the truth tables for both kinds of flip-flops
Explanation:
An SR flip flop is like a light switch. Set turns it 'on' and reset turns it 'off'
A D type flip-flop is a clocked flip-flop which has two stable states. A D type flip-flop operates with a delay in input by one clock cycle.
D type flip-flops are easily constructed from an SR flip-flop by simply connecting an inverter between the S and the R inputs so that the input to the inverter is connected to the S input and the output of the inverter is connected to the R input.
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.
That is a true statement. Hope this was helpful!
