Machine learning is an application of Artificial Intelligence that supports an architecture with the capability to learn and enhance from experience without being definitely programmed automatically.It can be used by search engines including Google and Bing to rank internet pages or to determine which advertisement to display to which user. It can be used by social networks including Facebook and Instagram to make a custom feed for each user or to tag the customer by the images that was uploaded.The classification of machine learning is as follows −Supervised Learning − Supervised learning is a type of machine learning method in ... Read More

There are various applications of machine learning which are as follows −Social media services − Machine learning is an essential role in personalizing news feed to superior advertisement focusing over social media. Facebook needs machine learning to display news feed to the user based on its interests by treating items clicked earlier by that user.Facebook always takes note of the friends that it can linked with, the profiles that it can visit, interests, workplace, and on the basis of this continuous learning, a file of Facebook users are suggested for us to become friends with.The Face Recognition nature of Facebook ... Read More

Machine learning is an application of Artificial Intelligence that supports an architecture with the capability to learn and enhance from experience without being definitely programmed automatically.It can be used by search engines including Google and Bing to rank internet pages or to determine which advertisement to display to which user. It can be used by social networks including Facebook and Instagram to make a custom feed for each user or to tag the customer by the images that was uploaded.It can be used by banks to identify whether an online transaction is fraudulent and by e-commerce websites including Amazon and ... Read More

Data Mining and Machine Learning are two fields which have influenced each other. Data mining is the field in which operations are performed on sets of data to determine certain patterns in the data sets, whereas machine learning uses certain algorithms that automatically improves the analysis processes through data based experiences. Although data mining and machine learning have many common things, they are quite different from each other. Read this article to learn more about Data Mining and Machine Learning and how they are different from each other. What is Data Mining? Data Mining is the process of discovering ... Read More

To successfully build a machine learning project, loading data properly is one of the most important as well as challenging tasks. CSV is the most common format for machine learning projects. It is a simple format which is used to store tabular data.Followings are the three most common approaches in Python with the help of which you can load CSV data for machine learning projects −Using Python Standard LibraryTo load CSV data files, Python standard library provides us with a built-in function namely csv module.ExampleIn this example we will be loading CSV data file of iris flower data set −#Importing ... Read More

In reinforcement learning methods, a trained agent interacts with a specific environment and takes actions based upon the current state of that environment.The working of reinforcement learning is as follows −First you need to prepare an agent with some specific set of strategies.Now leave the agent to observe the current state of the environment.Based on the agent's observation, select the optimal policy, and perform suitable action.Based on the action taken, the agent will get reward or penalty.Update the set of strategies used in step 1, if needed. Repeat the process from step1-4 until the agent learns and adopts the optimal ... Read More

Unsupervised learning methods, (opposite to supervised learning methods) do not require any labels or responses along with the training data. Unsupervised ML algorithms learn patterns and relationships from the given raw data. Although these methods may have lots of uncertainties in the result, we can always obtain some useful information such as all kinds of unknown patterns in the data, and the useful features for categorization.Unsupervised algorithms are called unsupervised because the machine learning model learns from data samples where the output is not known in advance.Let’s make it clearer, suppose we have, Input variables − mBut as opposed to ... Read More

Supervised learning, one of the most used methods in ML, takes both training data (also called data samples) and its associated output (also called labels or responses) during the training process. The major goal of supervised learning methods is to learn the association between input training data and their labels. For this it performs multiple training data instances.Let’s understand its working with the help of below given example −Suppose we have, Input variables − m andOutput variable − NThe mapping function from the input to output is as follows −𝑁 = 𝑓(𝑚)To learn such mapping function, we need an algorithm ... Read More

There are four learning styles in machine learning algorithms. Let’s have a look at them −Supervised LearningSupervised learning, one of the most used methods in ML, takes both training data (also called data samples) and its associated output (also called labels or responses) during the training process. The major goal of supervised learning methods is to learn the association between input training data and their labels. For this it performs multiple training data instances.Based on machine learning based tasks, we can divide supervised learning algorithms in two classes namely Classification and Regression.Unsupervised LearningUnsupervised learning methods, (opposite to supervised learning methods) ... Read More

The Python ecosystem, growing at a rapid pace day by day, became the dominant platform for machine learning. Here we will discover the most useful components of the Python ecosystem for machine learning. Let’s get started.SciPySciPy, pronounced as “Sigh Pie”, is an ecosystem of Python open-source libraries for performing Mathematical, Scientific, and Engineering computations. SciPy is comprised of the following core packages relevant to machine learning −NumPy − NumPy is a base N-dimensional array package for SciPy that allows us to efficiently work with data in arrays.Matplotlib − Matplotlib is used to create comprehensive 2-D charts and plots from data.Pandas ... Read More