Looking For Best Machine Learning Course!


Intellipaat offers an industry-specific Best Machine Learning course that mainly focuses on key modules such as Python, Algorithms, Statistics & Probability, Supervised & Unsupervised Learning, Decision Trees, Random Forests, Linear & Logistic regression, etc. Machine learning is enabling computers to tackle tasks that have, until now, only been carried out by people. From driving cars to translating speech, machine learning is driving an explosion in the capabilities of artificial intelligence –helping software make sense of the messy and unpredictable real world.

Why Machine Learning?

To better understand the uses of machine learning , consider some of the instances where machine learning is applied: the self-driving Google car, cyber fraud detection, online recommendation engines—like friend suggestions on Facebook , Netflix showcasing the movies and shows you might like, and “more items to consider” and “get yourself a little something” on Amazon—are all examples of applied machine learning.

We can use nowadays Superwised  Learning, Amazon uses superwised

Learning algorithms to predict what items the user may like based on the purchase

History of similar classes of users.


Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. Machine Learning, as the name suggests, provides machines with the ability to learn autonomously based on experiences, observations, and analyzing patterns within a given data set without explicitly programming.

We can say that machine learning is a modern innovation that has helped man enhance, not only man but also many industrial and professional process, it also advances everyday leaving. Machine learning has been used in multiple fields and industries like medical diagnosis, image processing, prediction, classification,

Learning association and even in regression.

Machine learning is helping in creating better technology to power today’s

An idea like, Image Recognition we can say it is one of the common use, we can use this in the case of  a black and white image where the intensity of each pixel is served as one of the measurements, we also have speech recognition, statistical arbitrage, financial services


Machine learning is generally split into two main categories: supervised and

unsupervised learning.

a) Supervised learning:

This approach basically teaches machines by example. By giving sufficient examples, a supervised-learning system would learn to recognize the clusters of pixels and shapes associated with each number and eventually be able to recognize

handwritten numbers, able to reliably distinguish between the numbers 9 and 4 or 6 and 8.

b) Unsupervised learning:

In contrast, unsupervised learning tasks algorithms with identifying patterns in data, trying to spot similarities that split that data into categories.






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