Survey machine learning and AI systems and tools you have used. Provide three ex
ID: 3742112 • Letter: S
Question
Survey machine learning and AI systems and tools you have used. Provide three examples of systems you encounter on a regular basis. For example, what machine learning algorithms are used by applications on your desktop, laptop and smartphone? What machine learning techniques are used by your favorite app or social media site? Research and determine the machine learning algorithms in use and any relevant details. Submit a one-page report with the following findings: 1. Devices, apps and sites surveyed 2. Machine learning and AI systems discovered 3. Attributes and other details learned about the systems in item 2 4. Are you surprised by any of the findings in 2 and 3. If so, why? Survey machine learning and AI systems and tools you have used. Provide three examples of systems you encounter on a regular basis. For example, what machine learning algorithms are used by applications on your desktop, laptop and smartphone? What machine learning techniques are used by your favorite app or social media site? Research and determine the machine learning algorithms in use and any relevant details. Submit a one-page report with the following findings: 1. Devices, apps and sites surveyed 2. Machine learning and AI systems discovered 3. Attributes and other details learned about the systems in item 2 4. Are you surprised by any of the findings in 2 and 3. If so, why? Survey machine learning and AI systems and tools you have used. Provide three examples of systems you encounter on a regular basis. For example, what machine learning algorithms are used by applications on your desktop, laptop and smartphone? What machine learning techniques are used by your favorite app or social media site? Research and determine the machine learning algorithms in use and any relevant details. Submit a one-page report with the following findings: 1. Devices, apps and sites surveyed 2. Machine learning and AI systems discovered 3. Attributes and other details learned about the systems in item 2 4. Are you surprised by any of the findings in 2 and 3. If so, why?Explanation / Answer
Machine Learning is a subset of AI wherein the algorithms use data to make decisions. Example: Pattern Matching, Recommendations, Predictions etc.
Real-time example: Predicting the Stock market price of a specific company, Facebook Newsfeed based on friend's history, browsed content etc.
There are various advanced machine learning algorithms used. But, even in the devices, apps, websites, we use frequently, ML algorithms are taking place. I am going to discuss few websites, apps, and devices that use ML techniques. There are many algorithms used in it. I am going to discuss few ML algorithms used by it.
1. Devices, apps, and sites surveyed
https://www.netflix.com/ - It is a website and also available as an app which uses many ML algorithms for providing recommendations to the user based on their activities. One of the algorithms it uses is Linear Regression. It is a supervised algorithm. (A supervised learning algorithm is a type of algorithm in which the data contains a class label. To understand this better, you are using the Netflix website for a while and Netflix has collected data regarding what kind of videos you are watching, it's genre, language etc. It also knows that you have chosen specific genre video. This 'specific' is known as a class label. Next time when you browse, it tries to predict based on these data). Coming to linear regression, it works based on a linear model. Based on one parameter, it tries to predict other.
Example: Based on your browsing history, it tries to predict the 'genre' of a video.
AccuWeather and other weather apps: Most of the weather algorithms use "Naive Bayes" ML algorithm. It is again supervised algorithm which uses conditional probability. For example, There are 10 tuples in the dataset which has Type of Weather, Celsius, Location and whether rained or not (Class Label). Using this data, it tries to predict for the given data for two probabilities, it will rain or not. The highest probability is the result.
Google Maps: Uses clustering algorithms for mapping the values based on geospatial data values.
Example: you want to build an ATM where the crowd is more, you need to choose the nearest place where many groups of people can use it. It uses a K-Means clustering algorithm
2. Machine learning and AI systems discovered
-> Supervised Learning Algorithms like Naive Bayes, Decision Tree.
-> Classification like Weather Prediction
-> Unsupervised Learning like Clustering
3. Attributes and other details learned about the systems in item 2
-> Dataset - The dataset used by the machine learning algorithms are divided into a training set and testing set. Training set means the algorithm rules are derived based on this data. Testing test means how well the algorithm performs based on training data. It mainly specifies the accuracy.
-> Data Cleaning - Usually the real-time data is noisy. It contains inconsistent values, missing values, data duplication etc. In order to apply algorithms, the data need to processed properly.
-> There are different ML tools used like R, Python, Weka etc by many websites.
4. Are you surprised by any of the findings in 2 and 3? If so, why?
-> Yes, I am very surprised. Never knew how our data is used wisely by these websites and apps. There are cutting-edge technologies used by these websites to provides things in an intelligent way.
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