Python Scipy sparse matrices explained

8 mins read What is a Sparse Matrix? Imagine you have a two-dimensional data set with 10 rows and 10 columns such that […]

Improvements in Deep Q-Learning with Python code: Dueling Double DQN, Prioritized Experience Replay, and Fixed Q-targets

28 mins read Deep Q-Learning was introduced in 2014. Since then, a lot of improvements have been made. So, today we’ll see four […]

Review of important offline evaluation metrics for recommendation systems

28 mins read We are in an era of personalization. The user wants personalized content and businesses are capitalizing on the same. Recommendation […]

Probability Density Estimation: Maximum Likelihood Estimation (MLE), Maximum A Posteriori (MAP), and Bayesian inference

14 mins read Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP) estimation are methods of estimating parameters of statistical models. Despite a […]

Implicit Recommender Systems with Alternating Least Squares

13 mins read In today’s post, we will explain a certain algorithm for matrix factorization models for recommender systems which goes by the […]

How to determine epsilon and MinPts parameters of DBSCAN clustering

9 mins read Every data mining task has the problem of parameters. Every parameter influences the algorithm in specific ways. DBSCAN (Density-Based Spatial […]

A review of Deep learning based recommendation systems

20 mins read INTRODUCTION The number of research publications on deep learning-based recommendation systems has increased exponentially in the past recent years. In […]

Steps to setup PyTorch with GPU for NVIDIA GTX 960m (Asus VivoBook n552vw) in Ubuntu

3 mins read In this post, I’m gonna describe the steps I used to utilize GPU for the PyTorch Deep Learning framework on […]

Restricted Boltzmann Machines (RBMs) Simply Explained

16 mins read Table of Content: Definition & Structure Reconstructions Probability Distributions Code Sample: Stacked RBMS Parameters & k Continuous RBMs Next Steps […]

A tutorial on the basics of Collaborative Filtering based Recommendations with Python implementation

29 mins read Collaborative Filtering is the most common technique used when it comes to building intelligent recommender systems that can learn to […]

Image classification example with Gradio and Keras

12 mins read Image classification is a subset of machine learning that categorizes a group of images into labeled classes. We train an […]

What is the Bias-Variance Trade-off?

9 mins read Whenever you are using a Statistical, Econometrical, or Machine Learning model, no matter how simple the model is, you should […]

Illustrated calculation of cross-entropy for binary, multi-class, and multi-label classification

8 mins read Cross-entropy is a commonly used loss function for classification tasks. Let’s see why and where to use it. We’ll start with […]

A complete tutorial on evaluation metrics for imbalanced classification

38 mins read A classifier is only as good as the metric used to evaluate it. If you choose the wrong metric to […]

Pandas data selection using .loc and .iloc

8 mins read When it comes to select data on a DataFrame, Pandas loc and iloc are two top favorites. They are quick, fast, easy to read, […]

Guidelines to use Transfer Learning in Convolutional Neural Networks

9 mins read Transfer learning involves taking a pre-trained neural network and adapting the neural network to a new, different data set. Depending […]

Kalman Filter Simply Explained

5 mins read Let’s start with what a Kalman filter is: It’s a method of predicting the future state of a system based […]

Walkthrough of an exploratory analysis for classification problems

20 mins read In this post, I’ll outline how to perform an exploratory analysis for a binary classification problem. I am going to […]

Dealing with imbalanced data in machine learning

8 mins read Imbalanced classes are a common problem in machine learning classification where there is a disproportionate ratio of observations in each […]

List of useful tutorials for Exploratory Data Analysis (EDA)

< 1 min https://towardsdatascience.com/exploratory-data-analysis-8fc1cb20fd15 https://medium.com/omarelgabrys-blog/statistics-probability-exploratory-data-analysis-714f361b43d1 https://www.kaggle.com/ekami66/detailed-exploratory-data-analysis-with-python https://www.kaggle.com/dvigneshwer/kernele7f4dbb964/notebook Visualizing the distribution of a dataset — seaborn 0.10.0 documentationhttps://seaborn.pydata.org/tutorial/distributions.html https://www.kaggle.com/kashnitsky/topic-1-exploratory-data-analysis-with-pandas https://iq.opengenus.org/exploratory-data-analysis-python/ Plotting with categorical data […]