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<meta property="og:title" content="">
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<meta property="og:site_name" content="">
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<meta property="og:url" content="">
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<meta property="og:description" content="Transform your prototype AI code into production-ready software.">
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<meta property="og:type" content="">
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<meta property="og:image" content=https://great-ai.scoutinscience.com/media/og-image.png>
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<style>
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.jupyter-wrapper a {
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color: var(--md-typeset-a-color) !important;
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</style>
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</head>
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<ul class="md-nav__list">
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<li class="md-nav__item">
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<a href="#the-training-notebook" class="md-nav__link">
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The training notebook
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<a href="#training-notebook" class="md-nav__link">
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Training notebook
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</a>
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</li>
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<li class="md-nav__item">
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<a href="#the-deployment-notebook" class="md-nav__link">
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The deployment notebook
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<a href="#deployment-notebook" class="md-nav__link">
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Deployment notebook
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</a>
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<li class="md-nav__item">
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<a href="../how-to-guides/install/" class="md-nav__link">
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Installation guide
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../how-to-guides/create-service/" class="md-nav__link">
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How to create a GreatAI service
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<li class="md-nav__item">
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<a href="../examples/simple/data/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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Simple example: data engineering
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../examples/simple/train/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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Optimise and train a model
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../examples/simple/deploy/" class="md-nav__link">
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Train a domain classifier on the semantic scholar dataset
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Hardening and deployment
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</a>
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<ul class="md-nav__list">
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<li class="md-nav__item">
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<a href="#the-training-notebook" class="md-nav__link">
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The training notebook
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<a href="#training-notebook" class="md-nav__link">
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Training notebook
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</a>
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</li>
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<li class="md-nav__item">
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<a href="#the-deployment-notebook" class="md-nav__link">
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The deployment notebook
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<a href="#deployment-notebook" class="md-nav__link">
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Deployment notebook
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</a>
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<a href="https://github.com/schmelczer/great-ai/edit/main/docs/tutorial/index.md" title="Edit this page" class="md-content__button md-icon">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
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<h1 id="train-and-deploy-a-sota-model">Train and deploy a SOTA model<a class="headerlink" href="#train-and-deploy-a-sota-model" title="Permanent link">#</a></h1>
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<p>Let's see GreatAI in action by going over the life-cycle of a simple service.</p>
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<p>Let's see <code>great-ai</code> in action by going over the life-cycle of a simple service.</p>
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<h2 id="objectives">Objectives<a class="headerlink" href="#objectives" title="Permanent link">#</a></h2>
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<ol>
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<li>You will see how the [great_ai.utilities][] can integrate into your Data Science workflow.</li>
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<li>You will use [great_ai.large_file][] to version and store your trained model.</li>
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<li>You will see how the <a href="/reference/utilities">great_ai.utilities</a> can integrate into your Data Science workflow.</li>
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<li>You will use <a href="/reference/large_file">great_ai.large_file</a> to version and store your trained model.</li>
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<li>You will use <a class="autorefs autorefs-internal" href="../reference/#great_ai.GreatAI">GreatAI</a> to prepare your model for a robust and responsible deployment.</li>
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</ol>
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<h2 id="overview">Overview<a class="headerlink" href="#overview" title="Permanent link">#</a></h2>
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<p><a class="md-button md-button--primary" href="deploy/"><span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M6 20a6 6 0 0 1-6-6c0-3.09 2.34-5.64 5.35-5.96A7.496 7.496 0 0 1 12 4a7.5 7.5 0 0 1 7.35 6A5.02 5.02 0 0 1 24 15a5 5 0 0 1-5 5H6M9.09 8.4 4.5 13l4.59 4.6 1.41-1.42L7.32 13l3.18-3.18L9.09 8.4m5.82 0L13.5 9.82 16.68 13l-3.18 3.18 1.41 1.42L19.5 13l-4.59-4.6Z"/></svg></span> Deploy it</a></p>
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</div>
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<h2 id="summary">Summary<a class="headerlink" href="#summary" title="Permanent link">#</a></h2>
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<h3 id="the-training-notebook">The <a href="train/">training notebook</a><a class="headerlink" href="#the-training-notebook" title="Permanent link">#</a></h3>
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<p>We load and preprocess the dataset while relying on [great_ai.utilities.clean][] for the heavy-lifting. Additionally, the preprocessing is parallelised using <a class="autorefs autorefs-internal" href="../reference/utilities/#great_ai.utilities.simple_parallel_map">great_ai.utilities.simple_parallel_map</a></p>
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<h3 id="training-notebook"><a href="train/">Training notebook</a><a class="headerlink" href="#training-notebook" title="Permanent link">#</a></h3>
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<p>We load and preprocess the dataset while relying on <a class="autorefs autorefs-internal" href="../reference/utilities/#great_ai.utilities.clean.clean">great_ai.utilities.clean</a> for doing the heavy-lifting. Additionally, the preprocessing is parallelised using <a class="autorefs autorefs-internal" href="../reference/utilities/#great_ai.utilities.simple_parallel_map">great_ai.utilities.simple_parallel_map</a></p>
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<p>After training and evaluating a model, it is exported using <a class="autorefs autorefs-internal" href="../reference/#great_ai.save_model">great_ai.save_model</a>.</p>
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<details class="tip">
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<summary>Remote storage</summary>
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<p>To store your model remotely, you need to set your credentials before calling <code>save_model</code>.</p>
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<p>For example, to use <a href="https://aws.amazon.com/s3/">AWS S3</a>:
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<p>For example, to use <a href="https://aws.amazon.com/s3" target="_blank">AWS S3</a>:
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<div class="highlight"><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="kn">from</span> <span class="nn">great_ai.large_file</span> <span class="kn">import</span> <span class="n">LargeFileS3</span>
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<a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a>
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<a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a><span class="n">LargeFileS3</span><span class="o">.</span><span class="n">configure</span><span class="p">(</span>
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@ -869,8 +897,9 @@
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<a id="__codelineno-0-11" name="__codelineno-0-11" href="#__codelineno-0-11"></a>
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<a id="__codelineno-0-12" name="__codelineno-0-12" href="#__codelineno-0-12"></a><span class="n">save_model</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="s1">'my-domain-predictor'</span><span class="p">)</span>
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</code></pre></div></p>
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<p>For more info, checkout <a href="/how-to-guides/configure-service">the configuration how-to page</a>.</p>
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</details>
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<h3 id="the-deployment-notebook">The <a href="deploy/">deployment notebook</a><a class="headerlink" href="#the-deployment-notebook" title="Permanent link">#</a></h3>
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<h3 id="deployment-notebook"><a href="deploy/">Deployment notebook</a><a class="headerlink" href="#deployment-notebook" title="Permanent link">#</a></h3>
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<p>We create an inference function that can be hardened by wrapping it in a <a class="autorefs autorefs-internal" href="../reference/#great_ai.GreatAI">GreatAI</a> instance.</p>
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<div class="highlight"><pre><span></span><code><a id="__codelineno-1-1" name="__codelineno-1-1" href="#__codelineno-1-1"></a><span class="kn">from</span> <span class="nn">great_ai</span> <span class="kn">import</span> <span class="n">GreatAI</span><span class="p">,</span> <span class="n">use_model</span>
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<a id="__codelineno-1-2" name="__codelineno-1-2" href="#__codelineno-1-2"></a><span class="kn">from</span> <span class="nn">great_ai.utilities</span> <span class="kn">import</span> <span class="n">clean</span>
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</code></pre></div>
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<ol>
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<li><a class="autorefs autorefs-internal" href="../reference/#great_ai.use_model">@use_model</a> loads and injects your model into the <code>predict_domain</code> function's <code>model</code> argument.
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You can freely reference it knowing that it is always given to the function.</li>
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You can freely reference it knowing that the function is always provided with it.</li>
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</ol>
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<p>Finally, we test the model's inference function through the GreatAI dashboard. <a href="/how-to-guides/use-service">The only thing left is to deploy the hardened-service.</a></p>
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<p>Finally, we test the model's inference function through the GreatAI dashboard. <a href="/how-to-guides/use-service">The only thing left is to deploy the hardened-service properly.</a></p>
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<div style="display: flex; justify-content: center;">
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<p><a class="md-button md-button--primary" href="/how-to-guides/create-service"><span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M18 22a2 2 0 0 0 2-2V4a2 2 0 0 0-2-2h-6v7L9.5 7.5 7 9V2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12Z"/></svg></span> Learn about all the features</a></p>
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<p><a class="md-button md-button--secondary" href="/examples/simple/data"><span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M7 2v2h1v14a4 4 0 0 0 4 4 4 4 0 0 0 4-4V4h1V2H7m4 14c-.6 0-1-.4-1-1s.4-1 1-1 1 .4 1 1-.4 1-1 1m2-4c-.6 0-1-.4-1-1s.4-1 1-1 1 .4 1 1-.4 1-1 1m1-5h-4V4h4v3Z"/></svg></span> Look at more examples</a></p>
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</div>
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<hr>
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<div class="md-source-file">
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<small>
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Last update:
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<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
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<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 12, 2022</span>
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</small>
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