Answer:
forces of production
Explanation:
Production forces relate to a concept used within the political economy which applies to the tangible means and manufacturing techniques for which workers create value and turn assets into selling things.
Production powers involve technical equipment and natural resources, and also the competitive capacities of manufacturing forces expressed by energy, skill, and information. This applies to a fusion of labor resources with a human labor force in Karl Marx own criticism of political philosophy.
Thus, from the above we can conclude that the conclude that the correct option is B.
I believe the answer is <span>. Decoy appliances/vehicles
The majority of this fraud is targeted the people who do not really pay attention to the specs of the product they use.
For example, many repairment targets older people by giving them advice to fix parts of their computer that's working fine.</span>
Answer:
Financial accounting is more highly regulated than managerial accounting.
Explanation:
Financial accounting is highly regulated and follows laid down principles that must be followed. International Financial Reporting Standard (IFRS) and Generally Accepted Accounting Principles (GAAP) are two examples of regulatory guidelines for financial accounting.
On the other hand managerial accounting is flexible and tailored to the manager's needs.
It must not follow the strict guidelines of financial accounting. This is because managerial accounting is used internally by a company and is not subject to public scrutiny.
Answer:
Supervised and Unsupervised Learning:
a. Unsupervised learning
b. Supervised learning
3. Supervised learning
4. Unsupervised learning
Explanation:
The key difference between supervised machine learning and unsupervised machine learning is that with supervised machine learning there is a training dataset (labeled data) on which the algorithm is trained to predict patterns. With unsupervised machine learning on the other hand, there is no training data. So, the algorithm discovers patterns on itself without reference to another labeled data or training dataset.
