Recurrent Neural Networks (RNN) with PyTorch

22 mins read Recurrent Neural Networks(RNNs) have been the answer to most problems dealing with sequential data and Natural Language Processing(NLP) problems for […]

Common regression loss functions with Python code

14 mins read All the algorithms in machine learning rely on minimizing or maximizing a function, which we call “objective function”. The group […]

Understanding Object Detection using YOLO with Python implementation

21 mins read Introduction How easy would our life be if we simply took an already designed framework, executed it, and got the […]

Understanding the fundamentals of Deep Learning and Convolution Neural Networks with Keras codes

55 mins read Introduction Did you know the first neural network was discovered in the early 1950s? Deep Learning (DL) and Neural Network […]

RCNN, Fast RCNN, and faster RCNN algorithms for Object Detection Explained

23 mins read Table of Contents A Simple Way of Solving an Object Detection Task (using Deep Learning) Understanding Region-Based Convolutional Neural Networks […]

PyTorch Graphs, Automatic Differentiation, and Autograd

14 mins read Table of content: Understanding Graphs, Automatic Differentiation, and AutogradBuilding Your First Neural NetworkGoing Deep with PyTorchMemory Management and Using Multiple […]

PyTorch Quick Tutorial

23 mins read Overview What is PyTorch? How can you get started with it from scratch? We’ll cover all of that in this […]

A tutorial on Histogram of Oriented Gradients (HOG) Feature Descriptor in Computer Vision with Python code

17 mins read Introduction Feature engineering is a game-changer in the world of machine learning algorithms. It’s actually one of my favorite aspects […]

Hough Transform implementation in Python

6 mins read The Hough transform (Duda and Hart, 1972), which started out as a technique to detect lines in an image, has been […]

A tutorial on Hough Transform

16 mins read Basics The Hough transform is an incredible tool that lets you identify lines. Not just lines, but other shapes as […]

A tutorial on Motion Estimation with Optical Flow with Python Implementation

26 mins read Recent breakthroughs in computer vision research have allowed machines to perceive their surrounding world through techniques such as object detection for detecting […]

Upper Confidence Bound (UCB) Algorithm Explained with Python code

7 mins read In this tutorial, I will explain to you the application of the Upper Confidence Bound(UCB) algorithm to solve the Multi […]

Difference between model-based and model-free reinforcement learning

3 mins read To answer this question, let’s revisit the components of an MDP, the most typical decision-making framework for RL. An MDP […]

Reinforcement Q-Learning from Scratch in Python with OpenAI Gym

24 mins read Most of you have probably heard of AI learning to play computer games on their own, a very popular example […]

What is q-learning?

5 mins read Introduction One of my favorite algorithms that I learned while taking a reinforcement learning course was q-learning. Probably because it […]

How to split data in decision tree nodes?

17 mins read The problem: We need to recommend apps to users according to what they’re likely to download Recommendation systems are one […]

Machine Learning From Scratch Series: Gradient Descent

9 mins read Gradient Descent is an iterative algorithm that is used to minimize a function by finding the optimal parameters. Gradient Descent can […]

Logistic Regression Implementation From Scratch in Python

4 mins read The objective of this tutorial is to implement our own Logistic Regression from scratch. This is going to be different […]

Machine Learning From Scratch Series: K-means Clustering: K-Nearest Neighbors (KNN) Algorithm

8 mins read Introduction A famous quote states: “You are the average of the five people you spend the most time with.” Although […]

What are Word Embeddings and how do they work? An introduction to Word2Vec (CBOW and Skip Gram)

22 mins read Word embedding is one of the most popular representations of document vocabulary. It is capable of capturing the context of […]