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In the current technological world, machine learning has become a buzzword to most program developers. Today's Lives have been automated from Google maps, assistant to Alexa, implying we have been using these applications in our daily lives.
With the great evolvement of machine learning, it has been extensively applied in the following fields:

ü  Speech recognition through a search by voice applications in Google.
ü  Recognition of the image by identifying digital images, persons, objects, or even places through automatic friend tag suggestion in social media platforms.
ü  Google maps through traffic recognition. This is through giving actual time location and the approximate time one can take to reach a specific location.
ü  Product recommendations that are through entertainment, machine learning where it recommends a product to the users.
ü  Malware filtering and email spamming where through machine learning the mails can easily be filtered from the important ones to spams and normal emails.


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·   Machine learning cases
·   Neural Network


Machine learning is associated with three critical types of algorithm models. Each algorithm has its benefits and disadvantages, but each has its parameters exclusively-readable patterns by machines. However, this requires extensive human intervention when it comes to labeling the data as unlabeled data only has none of the parameters in a readable form. Therefore, machine learning is classified into 3 key types, as mentioned below.
·   Unsupervised Learning: The unsupervised earning model works with unlabeled data implying that too much human labor is not required since m9ost of the datasets are operated by programs.
·   Reinforcement Learning: This machine learning model takes inspiration on how human runs their lives. This machine learning model improves upon itself by learning how situations can be made favorable through trial and error methods.
·   Supervised Learning: This type of machine learning where the algorithm operates under labeled data. Even though the data needs to be accurately labeled, machine learning is the most potent algorithm only if used under the right circumstances.


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The machine learning algorithms encompass programs that utilize both math and logic. The machine learning algorithms can adjust themselves in better performance owing to their exposure to data. Therefore, learning algorithms imply that anytime these programs can adequately process data over time, the same way humans change when they process data through learning.
With the massive growth we're experiencing in all fields and technological developments, machine learning has played an enormous role in making everything almost impossible through affordable data storage, the quantity of available data, and the development of more powerful and cheap data processing. Companies and organizations extensively utilize machine learning to dramatically affect the results drawing to limitless possibilities for the organization's operations.


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