Author: Rahul Khanna

MachineX: Genetic Algorithm

Genetic algorithm is based on the Charles Darwin famous principle of survival of the fittest, where the fittest of the individuals are given higher importance and are chosen for reproduction in order to produce children for the new generation. The process starts by selecting the fittest individuals from a population, who then produce offspring which inherit the characteristics of the parents. Since the parents already Continue Reading

MachineX: Evaluation Metrics for a Regression ML Model

In this blog post, we will quickly look at the various metrics to evaluate our regression models. But first, let us briefly discuss one of the best-known model evaluation approach we use which is Train-Test or also known as Train-Validation split. Train-Test Split: In this approach, we split the data into two parts known as Training set and Test set. The model is then trained Continue Reading

MachineX: SVM as Non-Linear Classifiers

In our previous blogs, we have already looked and had a higher level understanding of SVM and why to choose SVM over other classifiers. In this blog post, we will look at a detailed explanation of how to use SVM for complex decision boundaries and build Non-Linear Classifiers using SVM. The primary method for doing this is by using Kernels. In linear SVM we find Continue Reading

MachineX: The inevitable Principal Component Analysis

In this blog post, we will look at an interesting feature extraction technique of Machine Learning known as Principal Component Analysis (PCA). PCA is one of the powerful techniques in dimensionality reduction, in fact, the de facto standard for human face recognition. Let’s first understand what is dimensionality reduction Dimensionality Reduction As an example let’s say we have a data set with many-many features(which is Continue Reading

MachineX: Cosine Similarity for Item-Based Collaborative Filtering

“A recommender system or a recommendation system (sometimes replacing “system” with a synonym such as platform or engine) is a subclass of information filtering system that seeks to predict the “rating” or “preference” a user would give to an item. “ – Wikipedia In simple terms a recommender system is where the system is capable of producing a list of recommendation with respect to an Continue Reading

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