Machine Learning Tutorial

What is Machine Learning? Machine Learning Life Cycle Python Anaconda setup Difference between ML/ AI/ Deep Learning Understanding different types of Machine Learning Data Pre-processing Supervised Machine Learning

ML Regression Algorithm

Linear Regression

ML Classification Algorithm

Introduction to ML Classification Algorithm Logistic Regression Support Vector Machine Decision Tree Naïve Bayes Random Forest

ML Clustering Algorithm

Introduction to ML Clustering Algorithm K-means Clustering Hierarchical Clustering

ML Association Rule learning Algorithm

Introduction to association Rule Learning Algorithm


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Difference between AI/ ML/ Deep Learning

Now a day’s people are very much confused with the terms called artificial intelligence, machine learning, and deep learning. For them, it seems to be that all these three concepts are exactly the same, but in reality, they are interrelated to each other but are not same. So, let’s see how they differ from each other;

Comparison between AIMLDeep Learning

Machine Learning

Before directly digging into the concept of machine learning, let’s first look at the term data mining. Basically, data mining is a practice that keeps on reviewing extensive data set and extracts some important information from that set only. So, it can be seen that machine learning works similarly as that of data mining or even we can say that it is one of kind of data mining.

“A subset of AI that contains some techniques permitting the computers to learn from past experiences without being programmed explicitly is what Machine Learning is.”

Machine learning is widely used by many big brands such as, online shopping apps like Amazon and Myntra etc in which they provide their customers with some suggestions based on their previous shopping or products reviewed, also Netflix gives recommendations to the users about the latest web series and shows that they would love to watch based on their previous watch and search history.

Deep Learning

Deep learning is a subpart of machine learning. It works in the same manner as that of machine learning does just the fact that it differs in terms of its ability.

In the case of Machine learning, the model becomes better while growing. If an error occurs, the programmers have to solve the issue by itself as the machine learning models require some supervision, but deep learning differs in this case as the model fixes itself. It did not require any help from the outside. A good example would be an automatic car driving system.

“Deep learning is a subset of machine learning used to decode complicated issues by learning from its own methods of computation.”

Artificial Intelligence

Machine learning and deep learning are further the subsets of artificial intelligence. AI is entirely different from ML and Deep learning. AI is hiking up so fast these days due to its concept that the machine has to imitate exactly like a human brain while solving the problems and learning. It has good potential to outperform for the company’s growth reinventing some new ideas by changing its way of work.

“An ability of a computer or machine to work the same as the human brain is called Artificial Intelligence.”

AI means to copy the human brain in such a way that it performs exactly how a human brain would in any particular situation by thinking and functioning just like a human. AI is still under growth but has achieved a lot by so far, and the best example to take into the account would be the Sophia an advancement of AI, Siri, etc. It does not need to be preprogrammed, and rather it uses algorithms which works for its intelligence. It incorporates Reinforcement learning, deep learning neural networks.