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<!DOCTYPE HTML>
<!--
Massively by HTML5 UP
html5up.net | @ajlkn
Free for personal and commercial use under the CCA 3.0 license (html5up.net/license)
-->
<html>
<head>
<title>Solomom Obong Portfolio</title>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=2, user-scalable=no" />
<link rel="stylesheet" href="assets/css/main.css" />
<noscript><link rel="stylesheet" href="assets/css/noscript.css" /></noscript>
</head>
<body class="is-preload">
<!-- Wrapper -->
<div id="wrapper" class="fade-in">
<!-- Intro -->
<div id="intro">
<div style="display: flex; flex-wrap:wrap">
<img src="/Images/pic 10.jpg" width="400px" height="400px" alt="solomon obong">
<h1>Solomon Obong<br />
</h1>
</div>
<p>Results driven-data scientist
with expertise in Data wrangling, Statistical analysis and Machine learning. With a strong background in Industrial Mathematics and Economics, I am an agile project leader with a passion for AI and a track record of delivering impactful solutions and achieving business objectives.
<a></a></p>
<ul class="actions">
<li><a href="#header" class="button icon solid solo fa-arrow-down scrolly">Continue</a></li>
</ul>
</div>
<!-- Header -->
<header id="header">
<a href="index.html" class="logo">DATA SCIENTIST</a>
</header>
<!-- Nav -->
<nav id="nav">
<ul class="links">
<li class="active"><a href="index.html">PROJECTS</a></li>
<li><a href="https://github.com/Solobong">GITHUB</a></li>
<li><a href="https://acrobat.adobe.com/link/track?uri=urn:aaid:scds:US:53859529-60ec-3c4e-aed4-f81a0a24f249">CV</a></li>
</ul>
<ul class="icons">
<li><a href="https://www.linkedin.com/in/Solomon-obong-791b8a227/" class="icon brands fa-linkedin"><span class="label">LinkedIn</span></a></li>
<li><a href="https://github.com/Solobong" class="icon brands fa-github"><span class="label">Github</span></a></li>
</ul>
</nav>
<!-- Main -->
<div id="main">
<!-- Featured Post -->
<center>
<article class="post featured">
<header class="major">
<h2><a href="#">CLUSTERING OF CUSTOMERS ACROSS EUROPE AND SOUTH AMERICA RETAIL STORES<br />
</a></h2>
</header>
<a href="#" class="image main"><img src="/Images/pic11.jpg" alt="" /></a>
<p>Analysed customer's behavior and applied clustering models in ML to refine analysis and segmentation core of marketing campaigns across retail stores in Europe and South America countries. </p>
<ul class="actions special">
<li><a href="https://github.com/Solobong/Customer-Segmentation-Clustering" class="button large">VIEW PROJECT</a></li>
</ul>
</article>
<!-- Posts -->
<section class="posts">
<article>
<header>
<h2><a href="#">E-COMMERCE CUSTOMER SEGMENTATION AND CUSTOMERS REVIEW IN BRAZIL<br />
</a></h2>
</header>
<a href="#" class="image fit"><img src="/Images/pic14.jpg" alt="" /></a>
<p>This project aimed to understand customer segments and reviews to provide actionable insights for improving the e-commerce platform's services and customer experience in Brazil. After a comprehensive analysis involving data cleaning and preprocessing, I utilized K-means clustering to segment customers based on their behaviors and interactions. Additionally, I employed Natural Language Processing (NLP) techniques to categorize and analyze sentiment from customer reviews. </p>
<ul class="actions special">
<li><a href="https://github.com/Solobong/E-commerce-Customer-segmentation-and-Sentiment-analysis-in-Brazil" class="button">view project</a></li>
</ul>
</article>
<article>
<header>
<h2><a href="#">TWEET REVIEWS<br />
</a></h2>
</header>
<a href="#" class="image fit"><img src="/Images/pic12.jpg" alt="" /></a>
<p>A personal project whereby I researched and analyzed chunks of sentiment reviews of Twitter users. Machine Learning classification models were used to determine a user expression such as happy, angry, sad, neutral and so on through their tweets. </p>
<ul class="actions special">
<li><a href="https://github.com/Solobong/-Test-of-Emotions-in-Texts-and-Written-Speeches" class="button">view project</a></li>
</ul>
</article>
<article>
<header>
<h2><a href="#">SENTIMENT ANALYSIS IN FACIAL EXPRESSIONS<br />
</a></h2>
</header>
<a href="#" class="image fit"><img src="/Images/pic13.jpg" alt="" /></a>
<p>Built a deep learning model to detect and classify facial expressions such as happy, angry, disgust, etc using the Convolutional Neural Networks algorithm for integration in company's website</p>
<ul class="actions special">
<li><a href="https://github.com/Solobong/Sentiment-Detection-in-Facial-Expressions" class="button">view project</a></li>
</ul>
</article>
<article>
<header>
<h2><a href="#">WINE QUALITY ANALYSIS<br />
</a></h2>
</header>
<a href="#" class="image fit"><img src="/Images/wine.jpg" alt="" /></a>
<p>A personal project designed to statistically analyse based on some general chemical properties in winemaking, the effect of these properties on the quality of the wine. </p>
<ul class="actions special">
<li><a href="https://github.com/Solobong/A-Statistical-Analysis-Of-Wine-Quality-Using-Ordinary-Least-Square-and-Tensorflow" class="button">view project</a></li>
</ul>
</article>
<article>
<header>
<h2><a href="#">Suicide Watch and Depression Analysis<br />
</a></h2>
</header>
<a href="#" class="image fit"><img src="/Images/help.jpg" alt="" /></a>
<p>Utilized python to curate 98% data from Suicide watch and depression posts, built and optimized NLP algorithms to demonstrate a remarkable 72.1% classification accuracy with Logistc regressions in order to give valuable insights to assist in mental health research and support initiaties. </p>
<ul class="actions special">
<li><a href="https://github.com/Solobong/Suicidewatch-and-Depression" class="button">view project</a></li>
</ul>
</article>
<article>
<header>
<h2><a href="#">Bank Customers Churn prediction Using Deep Learning; Keras and tensorFlow<br />
</a></h2>
</header>
<a href="#" class="image fit"><img src="/Images/pic15.jpg" alt="" /></a>
<p>Developed a predictive model to identify bank customers likely to churn using machine learning and deep learning techniques. Preprocessed data, conducted exploratory analysis, and addressed class imbalance using SMOTE. Achieved balanced F1-scores and improved accuracy, providing valuable insights for customer retention strategies. </p>
<ul class="actions special">
<li><a href="https://github.com/Solobong/Bank-Custmers-Churn-Prediction-Using-Deep-Learning-Technique-Keras-and-Tensorflow-" class="button">view project</a></li>
</ul>
</article>
</center>
<!-- Footer -->
</div>
</footer>
</div>
<!-- Footer -->
<footer id="footer">
<section>
<form method="post" action="#">
<div class="fields">
<div class="field">
<label for="name">Name</label>
<input type="text" name="name" id="name" />
</div>
<div class="field">
<label for="email">Email</label>
<input type="text" name="email" id="email" />
</div>
<div class="field">
<label for="message">Message</label>
<textarea name="message" id="message" rows="3"></textarea>
</div>
</div>
<ul class="actions">
<li><input type="submit" value="Send Message" /></li>
</ul>
</form>
</section>
<section class="split contact">
<section class="alt">
<h3>Address</h3>
<p>Lagos, Nigeria<br />
</p>
</section>
<section>
<h3>Phone</h3>
<p><a href="#">(+234) 815-231-4848</a></p>
</section>
<section>
<h3>Email</h3>
<p><a href="#">obongsolomon96@gmail.com</a></p>
</section>
<section>
<h3>Social</h3>
<ul class="icons alt">
<li><a href="https://www.linkedin.com/in/Solomon-obong-791b8a227" class="icon brands alt fa-linkedin"><span class="label">LinkedIn</span></a></li>
<li><a href="https://www.github.com/Solobong" class="icon brands alt fa-github"><span class="label">Github</span></a></li>
</ul>
</section>
</section>
</footer>
<!-- Copyright -->
<div id="copyright">
<ul><li>© Solomon </li><li>SolobongDesign: <a href="obongsolomon96@gmail.com">Solomon Francis</a></li></ul>
</div>
</div>
<!-- Scripts -->
<script src="assets/js/jquery.min.js"></script>
<script src="assets/js/jquery.scrollex.min.js"></script>
<script src="assets/js/jquery.scrolly.min.js"></script>
<script src="assets/js/browser.min.js"></script>
<script src="assets/js/breakpoints.min.js"></script>
<script src="assets/js/util.js"></script>
<script src="assets/js/main.js"></script>
</body>
</html>