Machine Learning blog posts

Machine learning, also known as best way to solve hard problems of this century. In these lists of posts, we will try to learn as much as possible about this and apply our learnings on the live data.

Machinelearning Posts

Normalizing or Standardizing distribution in Machine Learning

How to Normalize or Standardize distribution in Machine Learning.

Machine learning for beginners - MP Neuron

Introduction to Neural Networks using MP neuron with full discussion on different things like threshold, loss function and learning algorithm.

Basic Mathematics for Neural Networks | Vectors and Matrices with Matplotlib

Vector and Matrices are at the heart of all Neural Networks. Today we are going to learn about vector and Matrix mathematics with the help of Matplotlib and numpy.


SVM | Introduction to Support Vector Machines with Sklearn in Machine Learning

SVM or support vector machines are supervised learning models that analyze data and recognize patterns on its own. They are used for both classification and regression analysis. In this post we are going to talk about Hyperplanes, Maximal Margin Classifier, Support vector classifier, support vector machines and will create a model using sklearn.

A simple mathematical guide to classification Trees using sklearn | Decision Trees

Classification tree beginner's explanation with Gini Index/ Gini Coefficient, Entropy, Information gain and sklearn and finally discussion on metrics of tree.

A practical approach to Tree Pruning using sklearn | Decision Trees

Tree pruning and finding prune subtree using cost complexity pruning or and finding optimal alpha value using sklearn


A Beginner's guide to Regression Trees using Sklearn | Decision Trees

Beginner's guide to Regression Trees including the equation, Pruning, Prediction using stratification of features in decision Trees using sklearn.

Introduction to KNN | K-nearest neighbor classification algorithm using Examples

Introduction to K-nearest neighbor( KNN) algorithm using sklearn. Using different distance metrics and why is it important to normalize KNN features?

How to choose a good evaluation metric for your Machine learning model

Evaluating your machine learning model can be done using accuracy, recall, precision, F1-score and/or mean absolute error or mean square error.

Data Science II - Introduction to Pandas

Pandas is an open source library built on the top of NumPy that allows us to analyse and clean the data for further step to be performed upon.


Data science I - Power up your NumPy array skills( Basics)

The first and foremost thing you need to get started in the data science and machine learning world is to have a little bit of knowledge of Python/ R.