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Hands-on Tutorial

Using transfer learning, you don’t need to build a convolutional neural network (CNN) from scratch

Nowadays, the growth of methods and algorithms in data science are increasing exponentially. Many companies begin adopting data science in their business. Many of them are for cost optimization, customer engagements, product developments, etc. In several cases, the implementation leads to computer vision.

Further, computer vision has many implementations, such…

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Hands-on Tutorial

SNAP is a package for large network analysis and manipulation written in C++ which can boost the calculations

The network is a collection of vertices connected by edges with a certain context. Whereas the graph is having no context. Both network and graph have characteristics — length, distances between two vertices, radius, diameter, etc.

In this short tutorial, we will explore how to find the diameter in a…

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Hands-on Tutorial

The performance comparison between Breadth-First Search and Depth-First Search for tree transversal

The idea behind this article came up when I was searching for an important file on my computer. In my mind, I asked myself, how can my computer search any files in a lot of folders? Before googling it, I tried to figure out the structures of computer’s drives. …

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Hands-on Tutorial

Simple but rich information of Monte Carlo simulation for stock and cryptocurrency price data

In this short article, you will learn the basic understanding of Monte Carlo simulation in the stock or cryptocurrency world. In the first section, you will learn about the theory behind the Monte Carlo. Then, we will implement the theory in the real world using Python.

For the best understanding…

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Hands-on Tutorial

Different initial cluster centroids will affect different results in the k-means cluster algorithm — How to determine the best one?

The k-means clustering algorithm is such an easy algorithm in unsupervised (clustering) to be implemented. To formulate the algorithm in manual calculation using mathematics is also quite simple.

However, behind its advantages, k-means has a limitation in its rule for choosing the cluster centroids. It is too sensitive to the…

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Hands-on Tutorial

The basic theory and implementation of walk-forward optimization as a cross-validation technique for time-series data

After reading this short article, you will absolutely understand the basic theory and implementation of walk-forward optimization for time-series data modelling. The common questions like why do the scientist must implement the walk-forward optimization on their time-series data will be answered.

Furthermore, in the last section, we will also demonstrate…

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Hands-on Tutorial

The basic theory and tutorial on how to simulate the central limit theorem and law of large numbers using R

Getting started with Statistics simulation using R

In Statistics, the central limit theorem and law of a large number have an important role, for instance in hypothesis testing. The central limit theorem states that the sample means will be normally distributed, it doesn’t depend on the population distribution, skewed or not. …

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Hands-on Tutorial

Understand the manual calculation of binary search and its implementation using Python

After reading this article, you will understand the comparison between linear search and binary search algorithms, how to perform searching tasks using linear and binary search algorithms, and why the binary search is known as the fastest searching algorithm.

To illustrate the mechanism of the searching algorithm, a detailed illustration…

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Hands-on Tutorial

How typo corrector can improve the string matching algorithm for matching the best string in the lexicon (master data)

After reading this short article, you will understand the implementation of graph theory for improving the string matching algorithm. For any typos in our writing, the typo corrector not only calculates the string similarities between the input and in the master database but also considers the distance between each character.

Audhi Aprilliant

Data Scientist. Tech Writer. Statistics, Data Analytics, and Computer Science Enthusiast. Portfolio & social media links at

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