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<!DOCTYPE HTML>
<!--
-->
<html>
<head>
<title>Portfolio - Livanshu Kashyap</title>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1, 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">
<h1>Livanshu Kashyap<br />
</h1>
<p><a href="https://"> Data Scientist</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">RESUME</a>
</header>
<!-- Nav -->
<nav id="nav">
<ul class="links">
<li class="active"><a href="index.html">PROJECTS</a></li>
<li><a href="generic.html">CERTIFICATIONS</a></li>
</ul>
<ul class="icons">
<li><a href="#" class="icon brands fa-linkedin"><span class="label">LinkedIn</span></a></li>
<li><a href="#" class="icon brands fa-github"><span class="label">GitHub</span></a></li>
</ul>
</nav>
<!-- Main -->
<div id="main">
<!-- Featured Post -->
<article class="post featured">
<header class="major">
<span class="date"> Graph ML </span>
<h2><a href="https://github.com/livanshu/Data_Science_Portfolio/tree/main/Projects/AML_TigerGraph_GSQL"> <u> AML Fraud Detection using Graph ML </u> <br />
</a></h2>
<p> • Dataset from <b> IBM AMLSimulator </b> with accounts, alerts and transactions data. <br>
• <b>TigerGraph: </b>Designed Schema, data-mapping and data loading. <br>
• <b>GSQL Queries</b> for Customer info, Community, Label Propagation and Page Rank.<br>
• <b>0.782 ROC</b> score with Decision Tree Classifier</p>
</header>
<a href="https://github.com/livanshu/Data_Science_Portfolio/tree/main/Projects/AML_TigerGraph_GSQL" class="image main"><img src="images/pic01.png" alt="" /></a>
<ul class="actions special">
<li><a href="https://github.com/livanshu/Data_Science_Portfolio/tree/main/Projects/AML_TigerGraph_GSQL" class="button large">LINK</a></li>
</ul>
</article>
<!-- Posts -->
<section class="posts">
<article>
<header>
<span class="date">Text Analysis</span>
<h2><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_Finetune_BERT_tensorflow/FineTuneBERT_Quora.ipynb">Fine Tune BERT on top of TensorFlow<br />
</a></h2>
</header>
<a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_Finetune_BERT_tensorflow/FineTuneBERT_Quora.ipynb" class="image fit"><img src="images/pic02.png" alt="" /></a>
<p> • Predicting Toxic and Non-Toxic Quora Questions using <b>BERT, keras & tf</b> <br>
• <b>100M </b> Parameters and <b>0.963</b> validation accuracy</p>
<ul class="actions special">
<li><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_Finetune_BERT_tensorflow/FineTuneBERT_Quora.ipynb" class="button">Link</a></li>
</ul>
</article>
<article>
<header>
<span class="date">Supervised, Unsupervised & Text</span>
<h2><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/fraud-detection.ipynb">Credit Card Fraud Detection <br />
</a></h2>
</header>
<a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/fraud-detection.ipynb" class="image fit"><img src="images/pic03.png" alt="" /></a>
<p> • <b>0.81 ROC</b> score with <b>KMeans & DBScan</b> on unlabelled data <br>
• <b>0.97 ROC</b> Score with <b>Voting Classifier</b> (LR, RF, DT) on labelled data <br>
• <b>Topic modelling</b> using LDA and pyLDAvis on text data </p>
<ul class="actions special">
<li><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/fraud-detection.ipynb" class="button">LINK</a></li>
</ul>
</article>
<article>
<header>
<span class="date">Supervised Learning</span>
<h2><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_DataCamp_Exam_submission/notebook.ipynb">Predicting product reviewers (owner/non-owner)<br />
</a></h2>
</header>
<a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_DataCamp_Exam_submission/notebook.ipynb" class="image fit"><img src="images/pic04.png" alt="" /></a>
<p> • <b>DataCamp</b> Certification project<br>
• Exploratory Data Analysis, <b>hyper parameter tuning</b> of XGB and SGD classifiers <br>
• <b>0.83 ROC</b> score with tuned XGBClassifier</p>
<ul class="actions special">
<li><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_DataCamp_Exam_submission/notebook.ipynb" class="button">LINK</a></li>
</ul>
</article>
<article>
<header>
<span class="date">Data Viz & Modelling</span>
<h2><a href="#">Interactive HR Dashboard and Attrition prediction<br />
</a></h2>
</header>
<a href="#" class="image fit"><img src="images/pic05.jpg" alt="" /></a>
<p></p>
<ul class="actions special">
<li><a href="#" class="button">LINK</a></li>
</ul>
</article>
<article>
<header>
<span class="date"> Regression </span>
<h2><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Housing_Price_Advanced_Regression/Project_house_price_advanced_regression_techniques_V1_1-4.ipynb"> Housing Price Prediction using advanced regression <br />
</a></h2>
</header>
<a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Housing_Price_Advanced_Regression/Project_house_price_advanced_regression_techniques_V1_1-4.ipynb" class="image fit"><img src="images/pic06.png" alt="" /></a>
<p> • <b>0.097 RMSE</b> on validation data using <b>GBRegressor</b> <br>
•Data Cleaning & Manipulation, EDA, Feature Engg., Hyperparameter tuning, Feature Importance
</p>
<ul class="actions special">
<li><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Housing_Price_Advanced_Regression/Project_house_price_advanced_regression_techniques_V1_1-4.ipynb" class="button">LINK</a></li>
</ul>
</article>
<article>
<header>
<span class="date"> CNN </span>
<h2><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_Keras_Classification.ipynb"> Flower Classification using Keras & Tensorflow<br />
</a></h2>
</header>
<a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_Keras_Classification.ipynb" class="image fit"><img src="images/pic07.png" alt="" /></a>
<p> • <b>0.73 Validation Accuracy </b> using customized CNN with 4M params and 10 layers <br>
• Used <b>data Augmentation & dropouts</b> </p>
<ul class="actions special">
<li><a href="https://github.com/livanshu/Data_Science_Portfolio/blob/main/Projects/Project_Keras_Classification.ipynb" class="button">LINK</a></li>
</ul>
</article>
</section>
<!-- Footer -->
<ul class="actions special">
<li><a href="#" class="button">See More (Github)</a></li>
</ul> <br>
<br>
</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>Toronto, ON<br />
</p>
</section>
<section>
<h3>Email</h3>
<p><a href="#">livanshu.kashyap@gmail.com</a></p>
</section>
<section>
<h3>Social</h3>
<ul class="icons alt">
<li><a href="https://www.linkedin.com/in/livanshu" class="icon brands alt fa-linkedin"><span class="label">LinkedIn</span></a></li>
<li><a href="https://livanshu.github.io" class="icon brands alt fa-github"><span class="label">GitHub</span></a></li>
</ul>
</section>
</section>
</footer>
<!-- Copyright -->
<div id="copyright">
<ul><li>© </li><li>Designed by: <a href="https://livanshu.github.io">LIVANSHU</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>
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<script src="assets/js/util.js"></script>
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</body>
</html>