Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn

Key Takeaways

hello everyone welcome to this tutorial by simply learn in this video you will learn about an interesting machine learning topic that is supervised versus unsupervised versus reinforcement learning let's discuss each of them in detail and understand when to use these algorithms along with their applications now there are a number of algorithms used in the field of machine learning to solve complex problems each of these algorithms can be classified into a certain category so the different types of machine learning algorithms are supervised learning unsupervised learning and reinforcement learning now let's look at the definition of each of these learning techniques supervised learning uses labeled data to train machine learning models label data means that the output is already known to you the model just needs to map the inputs to the outputs an example of supervised learning can be to train a machine that identifies the image of an animal below you can see we have a trained model that identifies the picture of a cat unsupervised learning uses unlabelled data to train machines unlabeled data means there is no fixed output variable the model learns from the data discovers patterns and features in the data and Returns the output here is an example of an unsupervised learning technique that uses the images of vehicles to classify if it's a bus or a truck so the model learns by identifying the paths of a vehicle such as the length and width of the vehicle the front and rear end covers roof hoods the types of Wheels used Etc based on these features the model classifies if the vehicle is a bus or a truck reinforcement learning trains a machine to take suitable actions and maximize reward in a particular situation it uses an agent and an environment to produce actions and rewards the agent has a start and an end state but there might be different parts for reaching the end State like a maze in this learning technique there is no predefined target variable an example of reinforcement learning is to train a machine that can identify the shape of an object given a list of different objects such as square triangle rectangle or a circle in the example shown the model tries to predict the shape of the object which is a square here now let's look at the different machine learning algorithms that come under these learning techniques some of the commonly used supervised learning algorithms are linear regression logistic regression support Vector machines K nearest neighbors decision tree random forest and knife base examples of unsupervised learning algorithms are K means clustering hierarchical clustering DB scan principal component analysis and others choosing the right algorithm depends on the type of problem you're trying to solve some of the important reinforcement learning algorithms are are Q learning Monte Carlo sarsa and deep Q Network now let's look at the approach in which these machine learning techniques work so supervised learning takes labeled inputs and Maps it to known outputs which means you already know the target variable unsupervised learning finds patterns and understands the trends in the data to discover the output so the model tries to label the data based on the features of the input data while reinforcement learning follows trial and error method to get the desired solution after accomplishing a task the agent receives an award an example could be to train a dog to catch the ball if the dog learns to catch a ball you give it a reward such as a biscuit now let's discuss the training process for each of these learning methods so supervised learning methods need external supervision to train machine learning models and hence the name supervised they need guidance and additional information to return the result unsupervised learning techniques do not need any supervision to train models they learn on their own and predict the output similarly reinforcement learning methods do not need any supervision to train machine learning models and with that let's focus on the types of problems that can be solved using these three types of machine learning techniques so supervised learning is generally used for classification and regression problems we'll see the examples in the next SL slide and unsupervised learning is used for clustering and Association problems while reinforcement learning is reward based so for every task or for every step completed there will be a reward received by the agent and if the task is not achieved correctly there will be some penalty used now let's look at a few applications of supervised unsupervised and reinforcement learning as we saw earlier supervised learning learning are used to solve classification and regression problems for example You can predict the weather for a particular day based on humidity precipitation wind speed and pressure values you can use supervised learning algorithms to forecast sales for the next month or the next quarter for different products similarly you can use it for stock price analysis or identifying if a cancer cell is malignant or benign now talking about the applications of unsupervised learning we have customer segmentation so based on customer Behavior likes dislikes and interests you can segment and cluster similar customers into a group another example where unsupervised learning algorithms are used as customer churn analysis now let's see what applications we have in reinforcement learning so reinforcement learning algorithms are widely used in the gaming Industries to build games it is also used to train robots to perform human tasks and with that we have come to the end of this video on supervised vers vers unsupervised versus reinforcement learning I hope you like this video If you enjoyed watching this video then please subscribe to the simply learn Channel and hit the Bell icon to never miss an update thank you for watching and keep learning hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos turn up and get certified click here