/
/

  • Home
  • Skills
  • About
  • Projects
  • Contact

Let's Connect

Makenson N.

Solving Problems with Code



Skills


React

React

NextJS

NextJS

NodeJS

NodeJS

TypeScript

TypeScript

Java

Java

Python

Python

JavaScript

JavaScript

HTML

HTML



About

Hello! I'm Makenson, a highly motivated and detail-oriented Full-Stack Software Engineer with a passion for crafting robust and user-friendly solutions.

My journey in the tech world began while pursuing an Associate in Arts On the STEM path at Broward College, I then transferred to Florida Atlantic University, where I declared my major and earned a Bachelor of Science in Computer Science.

I've been actively involved in delivering custom websites using Next.js, React, JavaScript, HTML, and CSS. I specialize in creating seamless, engaging web experiences

Awards & Certifications: Awarded Best Accessibility App at PlutoHacks.
Bachelor of Science in Computer Science from Florida Atlantic University.
Certified in Deep Learning Onramp and Machine Learning Onramp by MathWorks.


/



Projects

/

Title: Hand Gesture Tracker

This is a Open Source hand gesture tracker using Python, OpenCV, TensorFlow.

/

Title: Thousandmen.co

This is a custom designed webapp an E-Commerce business using Shopify & JavaScript.

/

Title: Amoseb.com

This is a custom designed drop shipping webapp for an E-Commerce business using Shopify & JavaScript.

/

Title: Mbjllc.store

This is a custom designed drop shipping web app for an E-Commerce business using Shopify & JavaScript.

/

Title: Lucien Lawn Services

This is a custom landing page using Next.js.

/

Title: Insitee.github.io

This is an award-winning wesbite for a hackathon using JavaScript, HTML, and CSS.



Tic Tac Toe




Project

Hand Gesture Tracker




Overview

I built this application in Python and it's source code is on GitHub. The Hand Tracker project is a Python-based solution that utilizes TensorFlow, OpenCV, Mediapipe, Matplotlib, and Scikit-Learn to recognize and interpret hand gestures in real-time. By leveraging deep learning with TensorFlow, the system accurately detects and classifies hand movements. OpenCV and Mediapipe provide the necessary tools for hand tracking and pose estimation. The project incorporates a graphical interface in Jupyter Notebook, enabling interactive visualization of the recognized gestures using Matplotlib. Hand Tracker serves as an invaluable tool for learning and communicating in American Sign Language, while also contributing to the fields of computer vision, gesture recognition, and human-computer interaction.

Technologies

Python

Jupyter Notebook

TensorFlow

OpenCV

Matplotlib

Mediapipe

Scikit-Learn

To-Do List

/
/

  • Home
  • Skills
  • About
  • Projects
  • Contact

Let's Connect

Gym Workout Tracker - Screenshot Results

/
/

  • Home
  • Skills
  • About
  • Projects
  • Contact

Let's Connect

Lower Body Day 1

WorkoutSetsReps
Warm Up2-5 mins
Quad Curls48-10
Hamstring Curls48-10
Leg Press48-10
Squats48-10
Deadlifts48-10
Calves310-12
Planks31:00 min
Cardio10-15 min

Upper Body Day

WorkoutSetsReps
Warm Up2-5 mins
Lat Pulldown45-8
Back Row45-8
Curls45-8
Tricep Press45-8
Bench press46-8
Dips48-10
Planks31:00 min
Cardio10-15 min

Lower Body Day 2

WorkoutSetsReps
Warm Up2-5 mins
Glute bridges410-12
Hip thrusts48-10
Walking lunges312-15
Single Leg Press312-15
Romain Deadlifts312-15
Hyper Extensions312-15
Planks31:00 min
Cardio10-15 min

Sudoku Game



Contact

/

Connect With Me