Machine Learning

Simulated Annealing Algorithm Explained from Scratch (Python)

  Simulated annealing algorithm is a global search optimization algorithm that is inspired by the annealing technique in metallurgy. In this one, Let’s understand the exact algorithm behind simulated annealing and then implement it in Python from scratch.   Get FREE pass to my next webinar where I teach how to approach a real ‘Netflix’ …

Simulated Annealing Algorithm Explained from Scratch (Python) Read More »

An Introduction to Gradient Boosting Decision Trees

Gradient Boosting is a machine learning algorithm, used for both classification and regression problems. It works on the principle that many weak learners(eg: shallow trees) can together make a more accurate predictor. How does Gradient Boosting Work? Gradient boosting works by building simpler (weak) prediction models sequentially where each model tries to predict the error …

An Introduction to Gradient Boosting Decision Trees Read More »

Gradient Boosting – A Concise Introduction from Scratch

Gradient Boosting is a machine learning algorithm, used for both classification and regression problems. It works on the principle that many weak learners (eg: shallow trees) can together make a more accurate predictor.   Get FREE pass to my next webinar where I teach how to approach a real ‘Netflix’ business problem, and how to …

Gradient Boosting – A Concise Introduction from Scratch Read More »

Feature image for Portfolio optimization

Portfolio Optimization with Python using Efficient Frontier with Practical Examples

Portfolio optimization in finance is the technique of creating a portfolio of assets, for which your investment has the maximum return and minimum risk.   Get FREE pass to my next webinar where I teach how to approach a real ‘Netflix’ business problem, and how to transition to a successful data science career.   Investor’s …

Portfolio Optimization with Python using Efficient Frontier with Practical Examples Read More »

Tensorflow

TensorFlow vs PyTorch – A Detailed Comparison

Compare the popular deep learning frameworks: Tensorflow vs Pytorch. We will go into the details behind how TensorFlow 1.x, TensorFlow 2.0 and PyTorch compare against eachother. And how does keras fit in here. Table of Contents: Introduction Tensorflow: 1.x vs 2 Difference between static and dynamic computation graph Keras integration or rather centralization What is …

TensorFlow vs PyTorch – A Detailed Comparison Read More »

Principal Component Analysis (PCA) – Better Explained

Principal Components Analysis (PCA) is an algorithm to transform the columns of a dataset into a new set of features called Principal Components. By doing this, a large chunk of the information across the full dataset is effectively compressed in fewer feature columns. This enables dimensionality reduction and ability to visualize the separation of classes …

Principal Component Analysis (PCA) – Better Explained Read More »

Feature Selection – Ten Effective Techniques with Examples

In machine learning, Feature selection is the process of choosing variables that are useful in predicting the response (Y). It is considered a good practice to identify which features are important when building predictive models. In this post, you will see how to implement 10 powerful feature selection approaches in R. Introduction 1. Boruta 2. …

Feature Selection – Ten Effective Techniques with Examples Read More »

Caret Package

Caret Package – A Practical Guide to Machine Learning in R

Caret Package is a comprehensive framework for building machine learning models in R. In this tutorial, I explain nearly all the core features of the caret package and walk you through the step-by-step process of building predictive models. Be it a decision tree or xgboost, caret helps to find the optimal model in the shortest …

Caret Package – A Practical Guide to Machine Learning in R Read More »

Top 15 Evaluation Metrics for Classification Models

Choosing the right evaluation metric for classification models is important to the success of a machine learning app. Monitoring only the ‘accuracy score’ gives an incomplete picture of your model’s performance and can impact the effectiveness. So, consider the following 15 evaluation metrics before you finalize on the KPIs of your classifier model. Introduction: Building …

Top 15 Evaluation Metrics for Classification Models Read More »

Logistic Regression with R

Logistic Regression – A Complete Tutorial With Examples in R

Logistic regression is a predictive modelling algorithm that is used when the Y variable is binary categorical. That is, it can take only two values like 1 or 0. The goal is to determine a mathematical equation that can be used to predict the probability of event 1. Once the equation is established, it can …

Logistic Regression – A Complete Tutorial With Examples in R Read More »

Course Preview

Machine Learning A-Z™: Hands-On Python & R In Data Science

Free Sample Videos:

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science