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What is CodeX?

CodeX is a medium publication that aims at providing top-notch content based on technology & coding.

We expect writers who submit their articles to CodeX must fall under the category of computer science, innovative technology, programming, coding & computer science concepts, personal experience in tech or coding, tech in major fields (like Healthcare, education, and so on).

Points to remember

  • Make sure that your article is a grammatical-error-free article (highly recommended to use Grammarly or its chrome extension).
  • Ensure that you have the rights to use the images that are posted on your article (Image source must be cited below the image). …


Creating and backtesting an SMA trading strategy in python

Photo by Markus Spiske on Unsplash

Disclaimer: This article is strictly for educational purposes and should not be taken as an investment tip.


With the increasing number of technological innovations, many industries deprecated their traditional methods and hoped-in to the latest tech ones to keep themselves updated. And so is the financial industry! In the past few years, there has been a lot going with the financial industry. An enormous amount of technological solutions for finance are invented and enhanced. In this article, we are going to see one of the notable technological innovations in finance which became a quantum leap to the stock trading space…


An easy way to access market data in few lines of code

Photo by Jamie Street on Unsplash

Downloading stock market data from the internet on every occasion is not a pleasant job. Also, it is not possible to get live prices when manually downloading data from the internet. This is when Cloud and APIs come into action.

Before diving into the coding part, let’s understand the mechanism of pulling stock data from a Cloud using an API. Assume that there is a company called IEX Cloud that owns or buys live stock market data directly from the exchanges. This company stores the data on its own database and hosts it via a cloud hosting platform i.e., making…


How I harnessed the power of an arising technology

Disclaimer: The products listed in this article should not be taken as a promotional activity

Nightmare of coding

I love to dream and I always dreamt of building a wonderful website with cool designs. While dreaming of building a website of my fantasies, it never failed to give me nightmares (Mephisto) on the vast amount of coding required to accomplish it. And that worried me a lot! When I thought of self-learning to build websites, the time required to master the skills gave me a myocardial infarction. I agree with the fact that we should be patient to show remarkable dexterity in developing websites but I don’t want to invest much time in learning while my competitors leave…


Familiarize the fundamentals of NumPy with practical implementation


NumPy is a python package that is primarily used for solving mathematical problems and high-level computations. It provides programmers with a wide variety of tools and built-in functions to create their own custom and complex functions to solve specific problems.

In this article, let’s familiarize the basics of NumPy by building some mathematical functions.

Function: 1 | Sigmoid

A Sigmoid function is a mathematical function that has a characteristic S-shaped curve. The Sigmoid function is normally used to refer specifically to the logistic function, also called the logistic sigmoid function.

All sigmoid functions have the property that they map the entire number line into…


It’s much easier than what you think it is

In recent days, there has been a lot of improvements in this modern technological world like autonomous cars, facial recognition systems, chatbots to name a few. These cool inventions are made possible only with the help of Deep Learning. Read this article to know what deep learning is and its supporting factors that made deep learning so popular.

Deep Learning

Deep learning is a subset of Machine Learning (ML) that gives us certain predictions for the given set of inputs by learning from examples or previous data points. That’s what the whole concept is about. Technically speaking, deep learning is the higher…


Learn to construct your own Python functions to solve geometrical problems without importing any packages


Coordinate Geometry also is known as Analytical Geometry or Cartesian Geometry, used to analyze or study geometry through the means of coordinates and vertices. This concept is held in much geometrical mathematics for example to find the area of geometrical shapes using coordinates, finding the midpoints, dividing a line segment into m:n ratio, and so on. Each of these concepts has its own formulas and methodology for solving the problems. What if we can solve these using python?

Python, being a general-purpose programming language, is highly powerful and efficient in solving mathematical tasks or problems. Even though there are several…


Learn to build and visualize K-means models to solve clustering problems

K-Means Clustering

The K-Means clustering beams at partitioning the ‘n’ number of observations into a mentioned number of ‘k’ clusters (produces sphere-like clusters). The K-Means is an unsupervised learning algorithm and one of the simplest algorithm used for clustering tasks. The K-Means divides the data into non-overlapping subsets without any cluster-internal structure. The values which are within a cluster are very similar to each other but, the values across different clusters vary enormously. K-Means clustering works really well with medium and large-sized data.

Despite the algorithm’s simplicity, K-Means is still powerful for clustering cases in data science. In this article, we are…


Using XGBoost, Random forest, KNN, Logistic regression, SVM, and Decision tree to solve classification problems


Assume that you are employed to help a credit card company to detect potential fraud cases so that the customers are ensured that they won’t be charged for the items they did not purchase. You are given a dataset containing the transactions between people, the information that they are fraud or not, and you are asked to differentiate between them. This is the case we are going to deal with. Our ultimate intent is to tackle this situation by building classification models to classify and distinguish fraud transactions.

Why Classification? Classification is the process of predicting discrete variables (binary, Yes/no…

Using Ridge, Bayesian, Lasso, Elastic Net, and OLS regression model for prediction


Estimating the sale prices of houses is one of the basic projects to have on your Data Science CV. By finishing this article, you will be able to predict continuous variables using various types of linear regression algorithm.

Why linear regression? Linear regression is an algorithm used to predict values that are continuous in nature. It became more popular because it is the best algorithm to start with if you are a newbie to ML.

To predict the sale prices we are going to use the following linear regression algorithms: Ordinal Least Square (OLS) algorithm, Ridge regression algorithm, Lasso regression…

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