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achive_more.php
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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<script src="js/navigationDE.js"></script>
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-143837547-1"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag() {
dataLayer.push(arguments);
}
gtag('js', new Date());
gtag('config', 'UA-143837547-1');
</script>
<meta charset="utf-8">
<meta content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=0" name="viewport" />
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1" />
<meta name="site" content="tvarit.com" />
<meta name="keywords"
content="SPS – Smart Production Solutions, Nuremberg, NürnbergMesse, Components, Control Technology, Drive Systems, Electromechanical Components, Human-Machine-Interface Devices, Industrial Communication, Industrial Software, Interface Technology, IPCs, Motion Control, Peripheral Equipment, Sensor Technology, " />
<meta name="description"
content="Tvarit AI is the best solution for smart manufacturing, smart machines and digital transformation" />
<meta name="keywords"
content="machine learning, free, no credit card, big data, machine learning, ml, machine learning as a service, machine learning API, API, datasets, models, decision trees, predictive models, predictions, fast predictions, evaluation, evaluate predictive models, ensembles, random decision forest, boosted trees, gradient boosted trees, gradient boosting, boosting ensembles, isolation forest, anomaly detector, anomaly score, clustering, k-means, g-means, cluster, centroids, linear regression, regression, logistic regression, lr, topic, topic modeling, topic distributions, PCA, principal component analysis, text analysis, LDA, Latent Dirichlet Allocation, partial dependence plot, scatter plot, time series forecasting, timeseries, forecast, trends, deepnets, deep learning, deep neural networks, neural network, neural networks, automl, automatic optimization, optiml, fusion, easy, model gallery, workflows, flatline, whizzml, dsl, domain-specific language, bindings, library, amazon echo, alexa, mac, desktop" />
<!-- Favicons -->
<link rel="apple-touch-icon" href="./assets/img/kit/free/apple-icon.png">
<link rel="icon" href="./img/favicon.png">
<title>Achieve More</title>
<link rel="stylesheet" href="css/bootstrap.min.css">
<link rel="stylesheet" href="css/style.css">
<link rel="stylesheet" href="css/responsive.css">
<link rel="stylesheet" href="css/flickity.css">
<link rel="stylesheet" href="css/animate.css">
<link
href="https://fonts.googleapis.com/css?family=Raleway:100,100i,200,200i,300,300i,400,400i,500,500i,600,600i,700,700i,800,800i,900,900i"
rel="stylesheet">
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<link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.6.3/css/all.css"
integrity="sha384-UHRtZLI+pbxtHCWp1t77Bi1L4ZtiqrqD80Kn4Z8NTSRyMA2Fd33n5dQ8lWUE00s/" crossorigin="anonymous">
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<![endif]-->
</head>
<body>
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<noscript><img alt="" src="https://secure.perk0mean.com/173652.png" style="display:none;" /></noscript>
<!------------------------ main menu start ---------------------->
<?php
include 'header.php';
?>
<!------------------------ main menu end ------------------------>
<!------------------------ header start ------------------------->
<header class="headerBg bgSizeCover achivemoreBg">
<div class="container">
<a href="#downClick" class="hdrscrollArrow"><i class="icon ion-ios-arrow-dropdown" style="color:#fff"></i></a>
<div class="row align-items-center">
<div class="col-md-6">
<div class="typography optiBgTrns" >
<div class="text-1" >
Achieve More
</div>
<div class="content">
<div class="text-big40">
with Tvarit AI Solutions</div>
</div>
<br>
</div>
</div>
</div>
</div>
</header>
<!------------------------ header end --------------------------->
<!------------------------ Automotives start --------------------->
<div class="section-padding" id="downClick">
<div class="container">
<div class="centerTitle">
<!-- <h3 class="bold text-center red mb-0">Achieve more with</h3> -->
<div class="innr-sec-mainTitle uppr">Tvarit <span class="red">AI</span> solution</div>
</div>
<br>
<br>
<div class="row achieveInfographic">
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<div class="col-md-4 order-1 order-md-1">
<div class="achieveWrapper upSet">
<ul class="ul-list-bullet">
<li>Business Use-Case identification</li>
<li>Break down the KPI
Objective</li>
<li>Data Extraction and
integration</li>
<li>Enablement of data
pipelines, workflows,
systems and
processes to facilitate
data science
operations</li>
</ul>
<div class="title-round title-round-grey">
Estimated time duration: <br >2 weeks(approx.)
</div>
</div>
</div>
<div class="col-md-4 order-3 order-md-2">
<div class="achieveWrapper upSet">
<div>
<div class="title-text">
Data <br class="d-none d-md-block">Harmonization:
</div>
<ul class="ul-list-bullet">
<li>
Tasks used to
ensure that the data
is complete and
relevant for
machine learning
purposes </li>
</ul>
</div>
<div class="title-round">
Week 2
</div>
</div>
</div>
<div class="col-md-4 order-5 order-md-3">
<div class="achieveWrapper upSet">
<div>
<div class="title-text">
AI <br class="d-none d-md-block">Driven:
</div>
<ul class="ul-list-bullet">
<li>
AI driven predictive analytics, root-cause, what-if analysis and set-points for controllers
</li>
</ul>
</div>
<div class="title-round">
Week 4
</div>
</div>
</div>
<div class="col-md-3 order-2 order-md-4">
<div class="achieveWrapper downSet">
<div class="title-round">
Week 1
</div>
<div class="title-text">
Data <br class="d-none d-md-block">Preparation:
</div>
<ul class="ul-list-bullet">
<li>
Tasks used to ensure
that the data fed into
and train machine
learning models are
clean and accurate</li>
</ul>
</div>
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<div class="col-md-3 order-4 order-md-5">
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Week 3
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Data <br class="d-none d-md-block">Labelling:
</div>
<ul class="ul-list-bullet">
<li>
Tasks used to ensure that the data has been properly labelled with the required output that needs to be learned
</li>
</ul>
</div>
</div>
<div class="col-md-3 order-6 order-md-6">
<div class="achieveWrapper downSet">
<div class="title-round title-round-grey">
Estimated time duration: <br >2 weeks(approx.)
</div>
<ul class="ul-list-bullet">
<li>Measurement of impact of AI driven decision in terms of both financial and non-financial benefits</li>
<li>Identification of closed-loop learnings to be incorporated into AI model</li>
</ul>
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