Fix html validation errors
This commit is contained in:
81
index.html
81
index.html
@@ -1,3 +1,5 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<head>
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<meta charset="utf-8" />
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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@@ -41,20 +43,21 @@
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<header>
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<header>
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<hgroup>
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<hgroup>
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<h1>Michael Pivato</h1>
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<h1>Michael Pivato</h1>
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<h2>Career summary and interests</h2>
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<p>Career summary and interests</p>
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</hgroup>
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</hgroup>
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</header>
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</header>
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<p>
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<p>
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A driven and highly motivated full-stack developer, I am always ready to
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A driven and highly motivated full-stack developer, I am always ready
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improve and learn. With a vast knowledge of multiple programming
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to improve and learn. With a vast knowledge of multiple programming
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languages, paradigms and related technicologies, I have successfully
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languages, paradigms and related technicologies, I have successfully
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implemented many applications that have been used and loved by clients.
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implemented many applications that have been used and loved by
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clients.
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</p>
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</p>
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<section id="career">
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<section id="career">
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<h2>Career</h2>
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<h2>Career</h2>
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<hgroup id="powerhealth">
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<hgroup id="powerhealth">
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<h3>PowerHealth Solutions</h3>
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<h3>PowerHealth Solutions</h3>
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<h4>2019 - Current</h4>
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<p>2019 - Current</p>
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</hgroup>
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</hgroup>
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<h4>Key Responsibilities</h4>
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<h4>Key Responsibilities</h4>
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<ul>
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<ul>
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@@ -64,8 +67,8 @@
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</li>
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</li>
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<li>
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<li>
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Create and maintain various front- and back-end components to
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Create and maintain various front- and back-end components to
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support consistent theming, quality, and developer experience across
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support consistent theming, quality, and developer experience
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PPM and now the billing product.
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across PPM and now the billing product.
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</li>
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</li>
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<li>
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<li>
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Respond to internal and client feedback to improve the costing
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Respond to internal and client feedback to improve the costing
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@@ -76,20 +79,20 @@
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<h4>Key Achievements</h4>
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<h4>Key Achievements</h4>
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<ul>
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<ul>
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<li>
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<li>
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Significant contributions to the redesigned costing product, that is
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Significant contributions to the redesigned costing product, that
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now in production use and enjoyed by clients.
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is now in production use and enjoyed by clients.
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</li>
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</li>
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<li>
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<li>
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Create and setup front-end and associated web server back-end
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Create and setup front-end and associated web server back-end
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components on the costing and billing products, as well as internal
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components on the costing and billing products, as well as
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products.
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internal products.
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</li>
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</li>
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</ul>
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</ul>
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<details id="dstgroup">
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<details id="dstgroup">
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<summary role="button" class="contrast">DST Group</summary>
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<summary role="button" class="contrast">DST Group</summary>
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<hgroup>
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<hgroup>
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<h4>Cadet at DST Group</h4>
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<h4>Cadet at DST Group</h4>
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<h5>2018 - 2019</h5>
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<p>2018 - 2019</p>
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</hgroup>
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</hgroup>
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<h5>Key Responsibilities</h5>
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<h5>Key Responsibilities</h5>
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<ul>
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<ul>
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@@ -108,8 +111,8 @@
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<ul>
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<ul>
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<li>Implementation of Raft algorithm for the camera network.</li>
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<li>Implementation of Raft algorithm for the camera network.</li>
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<li>
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<li>
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Implementation of Hand Detection using CNN, and finger recognition
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Implementation of Hand Detection using CNN, and finger
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with alternative algorithm.
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recognition with alternative algorithm.
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</li>
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</li>
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</ul>
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</ul>
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</details>
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</details>
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@@ -117,7 +120,7 @@
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<summary role="button" class="contrast">Kilburn Software</summary>
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<summary role="button" class="contrast">Kilburn Software</summary>
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<hgroup>
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<hgroup>
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<h4>Software Developer at Kilburn Software</h4>
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<h4>Software Developer at Kilburn Software</h4>
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<h5>2016 - 2018</h5>
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<p>2016 - 2018</p>
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</hgroup>
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</hgroup>
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<h5>Key Responsibilities</h5>
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<h5>Key Responsibilities</h5>
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<ul>
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<ul>
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@@ -147,7 +150,7 @@
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<h2>Education</h2>
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<h2>Education</h2>
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<hgroup>
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<hgroup>
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<h3>Bachelor of Information Technology</h3>
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<h3>Bachelor of Information Technology</h3>
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<h4>2016 - 2018</h4>
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<p>2016 - 2018</p>
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</hgroup>
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</hgroup>
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<p>University of South Australia</p>
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<p>University of South Australia</p>
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<p>GPA: 6.89</p>
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<p>GPA: 6.89</p>
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@@ -167,7 +170,9 @@
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<h3 id="technical">Technical</h3>
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<h3 id="technical">Technical</h3>
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<ul>
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<ul>
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<li>Java - Gradle, JUnit, Jooq, Swing</li>
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<li>Java - Gradle, JUnit, Jooq, Swing</li>
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<li>Angular and Web - including Typescript/Javascript, CSS, HTML</li>
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<li>
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Angular and Web - including Typescript/Javascript, CSS, HTML
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</li>
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<li>SQL - primarily MSSQL/T-SQL</li>
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<li>SQL - primarily MSSQL/T-SQL</li>
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<li>Rust</li>
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<li>Rust</li>
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<li>Flutter/Dart</li>
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<li>Flutter/Dart</li>
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@@ -198,8 +203,9 @@
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which includes this page!
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which includes this page!
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</p>
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</p>
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<p>
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<p>
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Recently my interesets have shifted slightly to large machine learning
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Recently my interesets have shifted slightly to large machine
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models, and have messed around with Stable Diffusion (mainly with
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learning models, and have messed around with Stable Diffusion
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(mainly with
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<a href="https://github.com/invoke-ai">Invoke AI</a>) and Llama
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<a href="https://github.com/invoke-ai">Invoke AI</a>) and Llama
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language models in
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language models in
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<a href="https://github.com/rustformers/llm">rustformers</a>. The
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<a href="https://github.com/rustformers/llm">rustformers</a>. The
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@@ -213,21 +219,23 @@
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<a href="https://gitea.michaelpivato.dev/vato007/coster-rs"
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<a href="https://gitea.michaelpivato.dev/vato007/coster-rs"
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>FastCoster</a
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>FastCoster</a
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>
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>
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project, where I reduced the time taken for processing some demo data
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project, where I reduced the time taken for processing some demo
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on the costing product from ~1.5 hours to ~7 seconds on a
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data on the costing product from ~1.5 hours to ~7 seconds on a
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laptop/desktop, or ~36 seconds on a smartphone. This was mainly due to
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laptop/desktop, or ~36 seconds on a smartphone. This was mainly due
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not using SQL Server, and using a custom algorithm in overhead
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to not using SQL Server, and using a custom algorithm in overhead
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allocation that significantly reduced memory consumption and the
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allocation that significantly reduced memory consumption and the
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number of required calculations.
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number of required calculations.
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</p>
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</p>
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<hgroup id="picar">
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<hgroup id="picar">
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<h3>PiCar</h3>
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<h3>PiCar</h3>
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<p>
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<a href="https://gitea.michaelpivato.dev/vato007/picar">Source</a>
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<a href="https://gitea.michaelpivato.dev/vato007/picar">Source</a>
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</p>
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</hgroup>
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</hgroup>
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<p>
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<p>
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This project originally involved communication between a Raspberry Pi
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This project originally involved communication between a Raspberry
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and a Traxxas Slash using the Pi's GPIO to control the steering and
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Pi and a Traxxas Slash using the Pi's GPIO to control the steering
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throttle of the RC Car. This was mounted on some 3D printed
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and throttle of the RC Car. This was mounted on some 3D printed
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brackets.The steering and throttle are set using an iPhone/Android
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brackets.The steering and throttle are set using an iPhone/Android
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application connected over WiFi.
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application connected over WiFi.
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</p>
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</p>
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@@ -238,9 +246,9 @@
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area and send this information to the controlling phone.
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area and send this information to the controlling phone.
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</li>
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</li>
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<li>
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<li>
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Depth Prediction: Using the Pi's camera and an Intel Neural Compute
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Depth Prediction: Using the Pi's camera and an Intel Neural
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Stick (NCS), the Pi could process camera data and use a custom
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Compute Stick (NCS), the Pi could process camera data and use a
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implementation of the
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custom implementation of the
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<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
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<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
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>FastDepth</a
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>FastDepth</a
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>
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>
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@@ -248,28 +256,30 @@
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</li>
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</li>
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</ul>
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</ul>
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<p>
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<p>
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Recently there have been efforts to port the backend to Rust, with the
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Recently there have been efforts to port the backend to Rust, with
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2D Lidar sensing and control completed. The Python BreezySLAM
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the 2D Lidar sensing and control completed. The Python BreezySLAM
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implementation is currently unfinished, mainly due to distractions
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implementation is currently unfinished, mainly due to distractions
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from other projects
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from other projects
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</p>
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</p>
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<hgroup id="depthprediction">
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<hgroup id="depthprediction">
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<h3>Depth Prediction</h3>
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<h3>Depth Prediction</h3>
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<p>
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<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
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<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
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>Source</a
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>Source</a
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>
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>
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</p>
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</hgroup>
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</hgroup>
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<p>
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<p>
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From the PiCar project, I explored many different implementations of
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From the PiCar project, I explored many different implementations of
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monocular depth Prediction and 3D SLAM solutions, including
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monocular depth Prediction and 3D SLAM solutions, including
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implementing my own algorithms and trainers for depth prediction that
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implementing my own algorithms and trainers for depth prediction
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perform well on constrained devices.
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that perform well on constrained devices.
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</p>
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</p>
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<p>
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<p>
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This gave me a solid foundation on Tensorflow/Keras and computer
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This gave me a solid foundation on Tensorflow/Keras and computer
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vision. It also helped expand my knowledge on machine learning from
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vision. It also helped expand my knowledge on machine learning from
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university/online study, as I previously had not explored models this
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university/online study, as I previously had not explored models
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large, or specifically computer vision related models.
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this large, or specifically computer vision related models.
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</p>
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</p>
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</section>
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</section>
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<footer class="container">
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<footer class="container">
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@@ -278,3 +288,4 @@
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</div>
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</div>
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</main>
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</main>
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</body>
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</body>
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</html>
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