mahtdev Goto Github PK

followers: 13.0 following: 12.0 repos: 71.0 gists: 0.0

Name: Miguel Hernandez

Type: User

Location: Mexico

🇺🇸

Hi! I am mahtdev

I am a highly experienced software developer with over 14 years in the industry. I specialize in full-stack development utilizing the following technologies:

Java
C#
Ruby
Node.js
Ruby on Rails
Angular
Spring
React

I am passionate about solving complex problems and am dedicated to staying up to date with the latest technologies and industry trends. I have a proven track record of delivering high-quality software on time and within budget. My experience in various projects has allowed me to be adaptable to changes and the needs of the client. I am committed to delivering the best possible solutions to my clients and strive for their complete satisfaction.

🇪🇸

Hola! Soy mahtdev

Soy un desarrollador de software con más de 14 años de experiencia en el campo. Mi especialidad es el desarrollo full-stack y he trabajado con las siguientes tecnologías:

Java
C#
Ruby
Node.js
Ruby on Rails
Angular
Spring
React

Me apasiona resolver problemas complejos y siempre estoy al día con las últimas tecnologías y tendencias del sector. Tengo un historial comprobado de entregar software de alta calidad a tiempo y dentro del presupuesto. Mi experiencia en diferentes proyectos me permite ser adaptable a los cambios y a las necesidades del cliente. Me comprometo a entregar las mejores soluciones a mis clientes y trabajo para lograr su completa satisfacción.

Miguel Hernandez's Projects

33-js-conceptos

📜 33 Conceptos que todo desarrollador de JavaScript debería saber.

3des

aes-encryption

Encripta la informacion en 256

apollo-server

🌍 Spec-compliant and production ready JavaScript GraphQL server that lets you develop in a schema-first way. Built for Express, Connect, Hapi, Koa, and more.

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

cerberus

home automation system

cliente-tcp

Componente que es cliente TCP/IP y permite la conexión a cualquier tipo de servidor

codigotutorial

Pasando Datos desde un Formulario de VB 2010 a Word

convertjuliandate

credit-card-fraud-detection

Apply statistical learning models to detect credit card fraud

credit-card-fraud-detection-1

The main objectives of this project are to predict fraudulent transactions from genuine ones and to understand the various attributes that help determine whether a credit card transaction is a fraudulent one or not. I processed the data using various statistical tools to address the imbalanced nature of our dataset. I used five classifier techniques: logistic regression, k-nearest neighbor, neural network, support vector machine and random forest for accurate predictions. Then, I used ensemble method of majority vote to improve our results by combining several models. Furthermore, I evaluated our ensemble model and further improved the accuracy with an advanced stacking method. Finally, I identified the best indicators of detecting fraudulent credit card transactions.

credit-card-fraud-detection-2

Prepared a statistically sound classification system for fraud detection in credit card transactions. Build classification models using Support Vector Machine and Random Forest Algorithm and achieved the F1 score of 0.69 and 0.76 respectively.