Random Forests are powerful ensemble machine learning algorithms that can perform both classification and regression. In machine learning, random forests work quite well in large and complex datasets. They can give high accuracy score. But we can improve these results even further. Therefore, in this article, we will learn how to perform hyperparameter tuning in […] ...

In the world of machine learning, there are numerous algorithms to choose from. Each algorithm has its own benefits and drawbacks and we should choose one that will work best for the data we have in hand. Random Forests are perhaps one of the best-known algorithms. In this article, we will learn about Random Forests […] ...

Learn how to implement Linear Regression for Machine Learning from scratch using Python. ...

Linear Regression is one of the most simple yet widely used statistical Machine Learning technique. The linear regression machine learning algorithm tries to map one or more independent variable (features) to a dependent variable (scalar output). In this post, you will be learning about: Different types of linear regression in machine learning. A bit of […] ...

In this part of the Deep Learning with Keras series, we will learn some of the most useful concepts. We will cover topics like Callbacks in Keras, saving models and restoring models. You will also learn about Tensorboard visualization which is an important part of Keras callbacks and analyzing and training models. This is the […] ...