Logistic Regression in Tensorflow with SMOTE

This blog discusses the implementation of Logistic Regression in TensorFlow to detect anomalies. Also, we will see how SMOTE (Synthetic Minority Over-sampling Technique) can be applied to generate additional data points for minority class.... [Read More]

Anomaly Detection, a short tutorial using Python

Anomaly detection is the problem of identifying data points that don't conform to expected (normal) behaviour. Unexpected data points are also known as outliers and exceptions etc. Anomaly detection has crucial significance in... [Read More]

Linear Regression in Tensorflow

Predicting house prices in Boston area

Tensorflow is an open source machine learning (ML) library from Google. It has particularly became popular because of the support for Deep Learning. Apart from that it's highly scalable and can run on Android. The documentation is well maintained and several tutorials available for different expertise levels. To... [Read More]

Implementing K-Means in Octave/Matlab

The K-means algorithm is the well-known partitional clustering algorithm. Given a set of data points and the required number of k clusters (k is specified by the user), this algorithm iteratively partitions the data into k clusters based on a distance function. Concretely, with a set of data... [Read More]