Machine Learning

Clustering categorical data using k-Mode Clustering

In Unsupervised Learning, Clustering is one of the most important and widely used classical machine learning algorithms. Although the k-Means Clustering Algorithm was invented by James MacQueen, way back in 1967, but even today it is being extensively employed for solving many significant business problems. But, the k-Means Clustering is…


Computer Vision plays a very crucial role in the field of Medical Science and this study of Applied Computer Vision in Medical Science is broadly known as Medical Imaging. Now, Computer Vision is achieved either by deploying Machine Learning or Deep Learning methodologies or both (hybrid) into production.

In this…


Let’s Get Started

Real-time data may have a vast number of attributes, which often makes essential Exploratory Data Analytics very difficult. Such data are known as highly Multi-Dimensional Data in which each and every attribute is referred to as a dimension. Moving ahead with Multi-Dimensional Data often results in:

  1. Lack of Proper Data…


Conceptually, Machine Learning (ML) is the art of teaching machines. Now, obviously teaching is such that when a student is taught by a teacher/tutor, he is capable of facing and answering any question which is either explicitly taught or not.

Real-Life Situation

Say, there is a subject covering m number of possible…


Machine Learning

Let’s detect the anomaly…

Anomaly Detection is a different variant of Machine Learning Problems that falls under Semi-Supervised Learning. It is Semi-Supervised because, in Anomaly Detection (also popularly known as Outlier Detection), models often involve parameters that are fit using the Validation Set labels whereas the training procedure does not involve Training Set labels…


Data Mining

In Data Science, imbalanced datasets are no surprises. If the datasets intended for classification problems like Sentiment Analysis, Medical Imaging or other problems related to Discrete Predictive Analytics (for example-Flight Delay Prediction) have an unequal number of instances (samples or data points) for different classes, then those datasets are said…


Learn, Code and Execute…

Naive Bayes is a very handy, popular and important Machine Learning Algorithm especially for Text Analytics and General Classification. It has many different configurations namely:

  1. Gaussian Naive Bayes
  2. Multinomial Naive Bayes
  3. Complement Naive Bayes
  4. Bernoulli Naive Bayes
  5. Out-of-core Naive Bayes

In this article, I am going to discuss Gaussian Naive…


Let’s Get Started…

There are many novels being written but among them, some acquire cult status over the years and are remembered for ages. The novels are of several genres and cross genres (mixture of several genres). Horror is one particular genre of novels. There are many famous horror novels, which are absolute…


Meaning, Significance, Implementation

Classification problems have been very common and essential in the field of Data Science. For example: Diabetic Retinopathy, Mood or Sentiment Analysis, Digit Recognition, Cancer-Type prediction (Malignant or Benign) etc. These problems are often solved by Machine Learning or Deep Learning. Also in Computer Vision, projects like Diabetic Retinopathy or…


Predicting the Attrition of Valuable Employees…..

In an IT firm, there are many Employee Architectures available. Some IT firms or at particular departments or certain levels follow the chief programmer structure, in which there is a “star” organisation around a “chief” position designated to the Engineer who best understands the system requirements.

While, some follow an…

Navoneel Chakrabarty

Data Mining | Data Analytics | Machine Learning | Financial Data Science | Natural Language Processing | Deep Learning

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