Unique Strings with Odd and Even Swapping Allowed
Introduction: In string manipulation, discovering unique strings amidst a sea of possibilities can be both challenging and rewarding. In this tutorial, we embark on a journey to unravel the secrets…
Applying SOLID Principles and Dependency Injection in Python
Introduction:In modern software development, adhering to principles and practices that promote maintainability, scalability, and reusability is crucial. Two fundamental concepts in this regard are the SOLID principles and dependency injection.…
Building a Regression MLP Using the Sequential API
Let’s switch to the California housing problem and tackle it using a regression neural network. For simplicity, we will use Scikit-Learn’s fetch_california_housing() function to load the data. This dataset is…
Logical Computations with Neurons | Deep learning
Warren McCulloch and Walter Pitts proposed a very simple model of the biological neuron, which later became known as an artificial neuron: it has one or more binary (on/off) inputs…
SQL Advanced | Wildcards
SQL Wildcard Examples We have the following “Persons” table: Using the % Wildcard Now we want to select the persons living in a city that starts with “sa” from the…
Beautiful Days at the Movies | Hackerrank Solutions
Lily likes to play games with integers. She has created a new game where she determines the difference between a number and its reverse. For instance, given the number 12,…
What is Stochastic Gradient Descent?
Stochastic Gradient Descent (SGD) is an optimization algorithm commonly used in machine learning for training models, particularly in large-scale and online learning settings. It is an iterative optimization algorithm that…
How to Extract Code from a Screenshot with 100% Accuracy?
Did you like an image containing code & take its screenshot? Now you want to copy the code from that screenshot, right? Panic not, because I’ve got you covered. In…
Quintile Analysis: Bringing it all togetherand making decisions
Introduction Quintile analysis is a statistical method used to divide a data set into five equal parts, each representing 20% of the total observations. This method is often used in…
SQL | The BETWEEN Operator
BETWEEN Operator Example The “Persons” table: Now we want to select the persons with a last name alphabetically between “Hansen” and “Pettersen” from the table above. We use the following…
SQL | The IN Operator
The IN operator allows you to specify multiple values in a WHERE clause. SQL IN Syntax: IN Operator Example The “Persons” table: Now we want to select the persons with…
Getting Started With Pandas | Part 1
Installation or Setup Detailed instructions on getting pandas set up or installed can be found here in the official documentation. Installing pandas with Anaconda Installing pandas and the rest of…
Selecting the Number of Clusters
With K-Means, you could use the inertia or the silhouette score to select the appropriate number of clusters, but with Gaussian mixtures, it is not possible to use these metrics…
SQL | The INSERT INTO AND UPDATE Statement
The second form specifies both the column names and the values to be inserted: SQL INSERT INTO Example We have the following “Persons” table: Now we want to insert a…
Tokenization in NLP
Word Level Tokenzation Splitting text into individual words “the quick brown fox” -> BUT Character Level Tokenization Splitting text into individual characters “the quick brown fox” -> But N-GRAM MODELS…
Appending to DataFrame | Pandas
Appending a new row to DataFrame import pandas as pd df = pd.DataFrame(columns = ) Appending a row by a single column value: df.loc = 1 df Appending a row,…
What is Exploratory Data Analysis (EDA)?
Exploratory Data Analysis (EDA) is an essential step in any data science project. It involves investigating and analyzing datasets to understand their characteristics, identify patterns, detect outliers, and uncover relationships…
Anomaly Detection using Gaussian Mixtures
Introduction Anomaly detection (also called outlier detection) is the task of detecting instances that deviate strongly from the norm. These instances are of course called anomalies or outliers, while the…
A Journey From Biological to Artificial Neurons
Surprisingly, ANNs have been around for quite a while: they were first introduced back in 1943 by the neurophysiologist Warren McCulloch and the mathematician Walter Pitts. In their landmark paper,…
Bayesian Gaussian Mixture Models
Rather than manually searching for the optimal number of clusters, it is possible to use instead the BayesianGaussianMixture class which is capable of giving weights equal (or close) to zero…