Found 664 Articles for Machine Learning

Introduction K-Medoids is an unsupervised clustering algorithm using the partition method of clustering. It is an improvised version of the K-Means clustering algorithm especially used to handle outlier data. It requires unlabeled data to work with. In this article let us understand the k-Medoids algorithm with an example. K-Medoids Algorithm In the K-Medoids algorithm, each data point is called a medoid. The medoids serve as cluster centers. The medoid is a point such that its sum of the distance from all other points in the same cluster is minimum. For distance, any suitable metric like Euclidian distance or Manhattan distance ... Read More

In today’s date, Artificial Intelligence has impacted our lives way in that nothing else could have impacted. It has changed how our daily jobs are done and has involvement in major areas of our industry, lives, and almost everything. Here in this article, we are going to see some areas in our lives where Artificial Intelligence has significantly played its role. Health Industry Healthcare is a growing and crucial industry in the 21st century. Not only it is providing a better life to people but also saving millions of lives every day. We just can't overlook the health aspect of ... Read More

Introduction The distribution of data gives us useful insights into the data while working with any data science or machine learning use case. Data Distribution is how the data is available and its present condition, the information about specific parts of the data, any outliers in the data as well as central tendencies related to the data. To explore the data distribution there popular graphical methods that prove beneficial while working with the data. In this article let us explore these methods. Know more about your data: The Graphical Way Histograms & KDE Density Plots Histograms are the most ... Read More

Introduction Categorical data is a type of data that takes a fixed number of values and there is no possible logical order in such variables. Categorical variables can be blood groups, yes-no situations, gender, ranking (ex. first, second, third), etc. Categorical variables most of the time undergo encodings such as one hot encoding, and nominal encoding to represent them in binary or integer format for the Machine Learning use case under consideration. Categorical Data and related terms Mode is the most common central tendency associated with categorical variables/observations. It is the value in the set of observations that has the ... Read More

Introduction Machine Learning is a diverse area with a wide range of applications in many domains. As far as we have an abundance of usable data and a problem to solve in a particular area, Machine Learning can do wonders. Machine Learning Projects can vary in terms of complexity from simple Regression tasks for predicting sales, and wine quality to complex tasks like Object Recognition, Autonomous Vehicles, and Reinforcement Learning. However, for someone who is a beginner in Machine Learning, the discussed below 5 projects can be highly useful. Predicting the Quality of Wine For folks who are a beginner ... Read More

The field of machine learning is experiencing rapid expansion, with cloud computing playing an increasingly vital role in supporting such applications. Cloud platforms present an extensive range of elements that facilitate the easy and seamless development, training, and deployment of machine learning models. In this comprehensive article, we will explore the leading cloud computing platforms used for machine learning. By meticulously comparing the distinctive features and advantages of each platform, we aim to equip us with valuable insights to help in the selection of the ideal platform that aligns with our specific requirements. Top Cloud Computing Platforms for Machine Learning ... Read More

In the rapidly changing field of artificial intelligence (AI), libraries for natural language programming (NLP) have a vital function in empowering developers to construct robust and smart applications. NLP libraries offer an extensive range of tools and assets that ease the handling and examination of human language, enabling machines to comprehend and react to written information. Within this article, we will delve into the finest ten NLP libraries that every AI developer should acquaint themselves with. By gaining an understanding of the capacities and characteristics of these libraries, we can harness their advantages to devise pioneering and remarkably effective applications ... Read More

As we know machine learning is increasing rapidly and is used by different industries that needs advanced tools and environments for model development and open-source online machine learning environments which have risen in its popularity because of their flexibity, accessibility and collaborative nature. In this article we will examine top five open-source online machine learning environments that are widely used and well-renowned in the area of machine learning. By the end of this particular article, we will have a full understanding of these environments and their importance in the field of machine learning. What is the Importance of Open-Source Online ... Read More

When it comes to the field of machine learning and artificial intelligence, classification models hold immense significance in deciphering extensive volumes of data. These models find extensive utilization across diverse domains, ranging from the identification of visual patterns and comprehension of human language to the identification of fraudulent activities and the division of customers into distinct groups. In this article, we will explore the advantages and drawbacks of various classification models, providing beginners with invaluable perspectives and information to enable them to make well-informed choices. Additionally, we will expand upon the topic by including additional insights and relevant details to ... Read More

The use of Artificial Intelligence (AI) in facial identification has completely transformed the computer vision field. This advancement allows machines to verify and distinguish individuals based on their distinct facial characteristics. This state-of-the-art technology employs algorithms for machine learning and deep learning components, aiding in the extraction of facial patterns and their comparison with a database of familiar faces. Facial identification has now become an essential aspect of our daily lives, finding extensive applications in personalized user experiences and security systems. This article explores the utilization of AI in facial recognition, its impact across various industries, and the different techniques ... Read More