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Machine learning is a subset of data science where machines learn automatically and make improvisations from past experiences. Machine learning is implemented at the ‘Modeling Phase’ and it is said that machine learning is an application of Artificial Intelligence (AI) that enables the systems to learn automatically.
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The main reason for developing the concept of machine learning is to have an automated process that will save time so that humans can be more focused on their time & energy on more complex decision making.
Machine learning is a great help in detecting all sorts of spam, predicts the maintenance of manufacturing industries. Another best thing about machine learning is that it will always recommend the right product to the end-user and along with this it also simplifies product marketing.
The main reason for developing the concept of machine learning is to have an automated process that will save time so that humans can be more focused on their time & energy on more complex decision making.
Machine Learning in Cloud
An overview of Machine Learning
Machine learning is a life-changing application and a sub-category of Artificial Intelligence (AI) that stresses upon designing the systems and allow them to learn from past experiences and make certain predictions without being openly programmed. There are three types of machine learning; Supervised, Unsupervised and Reinforced learning. Various kinds of problems can be solved by machine learning with ease like face recognition, face detection, speech recognition, object recognition and etc.
Why machine learning is used in cloud in the first place?
While working with the system of machine learning, you’ll encounter a huge amount of data and instead of using the local infrastructure of machine learning it is better to use an online infrastructure since it has the availability of a number of machines and has hard disk capabilities as well.
Another reason of using machine learning in the cloud is that it has instant availability of thousands of nodes or servers in a short span of time.
The usage of cloud infrastructure in machine learning has made it easy to do the prototyping at a fast rate. If the user wants to perform with a small amount of data then it can be deployed easily & with greater speed and get a certain result. In the case of the bad distance then the procedure of prototyping will continue to process until you are provided with better results.
The main reason of using the cloud is that machine learning lacks professionally and since there is already the availability of data in different systems of online machine learning in the cloud that does not require very highly professional data scientists and making the cloud very useful for machine learning.
There is no requirement of any local infrastructure because there are thousands of machines that are available.
So, the above mentioned are some of the reasons for using the cloud in machine learning. Now, let’s see what are the online services are there that are made available.
1. Google Cloud Platform
2. Microsoft Azure
3. Big ML
4. Amazon Machine Learning
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Machine learning has algorithms that are used for the purpose of learning and these algorithms are broadly classified into two types; Supervised Algorithm and Unsupervised Algorithm. The supervised algorithm is comprised of Linear Regressions, Logistic Regression, KNN Classification whereas the unsupervised algorithm is comprised of K-Means Clustering only.
Machine learning has algorithms that are used for the purpose of learning and these algorithms are broadly classified into two types; Supervised Algorithm and Unsupervised Algorithm. The supervised algorithm is comprised of Linear Regressions, Logistic Regression, KNN Classification whereas the unsupervised algorithm is comprised of K-Means Clustering only.
