Pivot, Melt, Stack, and Unstack methods in Pandas

5 mins read Data does not come in a usable format by default; a data science professional has to spend 70–80% of their […]

Python testing tutorial using pytest

18 mins read Testing your code brings a wide variety of benefits. It increases your confidence that the code behaves as you expect and […]

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 […]

Machine Learning From Scratch Series: Linear Regression with Gradient Descent

10 mins read In the following sections, we are going to implement linear regression in a step-by-step fashion using just Python and NumPy. We will […]

Machine Learning From Scratch Series: Logistic Regression

10 mins read In this article, we are going to implement the most commonly used Classification algorithm called Logistic Regression. First, we will […]

Data Representation in NumPy

12 mins read The NumPy package is the workhorse of data analysis, machine learning, and scientific computing in the python ecosystem. It vastly simplifies manipulating […]

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 […]

Common loss functions for training deep neural networks in PyTorch

17 mins read Neural networks can do a lot of different tasks. Whether it’s classifying data, like grouping pictures of animals into cats […]

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 […]

Exploratory Data Analysis (EDA) example: Road safety dataset case study

20 mins read Getting a good feeling about a new dataset is not always easy and takes time. However, a good and broad […]

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, […]

Styling Pandas DataFrames using Style API

10 mins read Python’s Pandas library allows you to present tabular data in a similar way as Excel. What’s not so similar is […]

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 […]

Using Kaggle Datasets in Google Colab

< 1 min Steps: Create an API key in Kaggle.To do this, go to kaggle.com/ and open your user settings page.  Next, scroll […]

Getting Started With Google Colab

5 mins read If you want to create a machine learning model but say you don’t have a computer that can take the […]

Understanding Gated Recurrent Unit (GRU) with PyTorch code

21 mins read The Gated Recurrent Unit (GRU) is the younger sibling of the more popular Long Short-Term Memory (LSTM) network, and also a […]

Understanding Long Short-Term Memory Networks (LSTM) with PyTorch codes

24 mins read LSTMs are a particular variant of RNNs, therefore having a grasp of the concepts surrounding RNNs will significantly aid your […]

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 […]

A complete guide to Python’s magic methods with example

33 mins read Introduction What are magic methods? They’re everything in object-oriented Python. They’re special methods that you can define to add “magic” […]