
Implementation of a Neural Network from scratch
Are you someone who is always fond of using machine learning and deep learning libraries such as Scikitlearn, TensorFlow, PyTorch, etc, but don’t really understand how a neural network works underneath the libraries? If so, this post tries its best to explain what a neural network is, how it works,...

Neural Network Basics with Logistic Regression
These are some of my notes taken from the first course of Deep Learning Specialization (Neural Networks and Deep Learning) by deeplearning.ai. This might help you gain insights on how a neural network is formed and how Logistic Regression is used to form one single neuron to stack up and...

RandomForest with scikitlearn  Part 2
Welcome to the second part of the post. In this half, we will be implementing RandomForest regressor on our own dataset. For that first, you will need to have a dataset. The one that I used is a weather dataset from my city (Kathmandu) which is available at this link....

RandomForest with scikitlearn (Part 1)
Among many machine learning techniques, RandomForest is one of the most widely used ensemble supervised algorithm for both classification and regression tasks. Yes, it works smoothly for both categorical and continuous prediction labels. Before diving into the code directly, let’s first discuss the theoretical aspects of RandomForest. It is an...

Dimensionality Reduction  Machine Learning
In Machine Learning or Statistics, dimensionality reduction is the process of reducing the number of random variables under consideration by obtaining a set of principal variables. This can be achieved using two processes: Feature Selection and Feature Projection Feature Selection Feature selection methods try to find a subset of the...