{"id":4574,"date":"2022-11-10T17:50:44","date_gmt":"2022-11-11T01:50:44","guid":{"rendered":"https:\/\/live-cometml.pantheonsite.io\/?p=4574"},"modified":"2025-04-24T17:16:29","modified_gmt":"2025-04-24T17:16:29","slug":"using-tensorflow-in-comet","status":"publish","type":"post","link":"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/","title":{"rendered":"Using TensorFlow in Comet"},"content":{"rendered":"\n<figure class=\"wp-block-image aligncenter\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/max\/700\/0*Lhfv0VDUl01absF3\" alt=\"\"\/><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p class=\"has-text-align-center\">Photo by&nbsp;<a class=\"au ll\" href=\"https:\/\/unsplash.com\/@agk42?utm_source=medium&amp;utm_medium=referral\" target=\"_blank\" rel=\"noopener ugc nofollow\">Alex Knight<\/a>&nbsp;on&nbsp;<a class=\"au ll\" href=\"https:\/\/unsplash.com\/?utm_source=medium&amp;utm_medium=referral\" target=\"_blank\" rel=\"noopener ugc nofollow\">Unsplash<\/a><\/p>\n\n\n\n<div class=\"ir is it iu iv\">\n<p id=\"21b6\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Neural Networks are a subset of artificial intelligence, aiming at modeling the human brain through mathematical concepts. A neural network is composed of a series of interconnected nodes, or neurons, that process information. Nodes are organized in more or less complicated layers.<\/p>\n<p id=\"de8d\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Neural networks can be used for a variety of tasks, such as pattern recognition and data classification. If the number of layers is greater than three, the neural network becomes a&nbsp;<strong class=\"bm mh\">deep learning<\/strong>&nbsp;network. Deep learning can be used to improve the accuracy of predictions made by neural network algorithms. However, it is also time-consuming and resource-intensive.<\/p>\n<p id=\"bb8f\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\"><strong class=\"bm mh\">TensorFlow<\/strong>&nbsp;is an open-source software library for training and deploying neural networks. It also provides a highly flexible framework for implementing deep learning models.<\/p>\n<p id=\"44f4\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">In this article, we will talk about how to integrate TensorFlow into&nbsp;<strong class=\"bm mh\">Comet<\/strong>.&nbsp;<a class=\"au ll\" href=\"https:\/\/heartbeat.comet.ml\/www.comet.com\" target=\"_blank\" rel=\"noopener ugc nofollow\">Comet<\/a>&nbsp;is an online platform that allows you to monitor and log experiments. Its main advantage is that it simplifies the process of evaluating metrics such as system metrics, parameters, and other stats.<\/p>\n<p id=\"ac3b\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">You can use Comet to build different experiments for the same project, and then compare each experiment\u2019s performance and determine which configurations perform the best. You can also use Comet to share your results with other people across your team or business.<\/p>\n<p id=\"ac0c\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">This article is organized as follows:<\/p>\n<ul class=\"\">\n<li id=\"b047\" class=\"mi mj iy bm b lo lp lr ls lu mk ly ml mc mm mg mn mo mp mq ga\" data-selectable-paragraph=\"\">Building a model in TensorFlow<\/li>\n<li id=\"119f\" class=\"mi mj iy bm b lo mr lr ms lu mt ly mu mc mv mg mn mo mp mq ga\" data-selectable-paragraph=\"\">Showing results in Comet<\/li>\n<\/ul>\n<h1 id=\"12c5\" class=\"mw mx iy bm my mz na nb nc nd ne nf ng kn nh ko ni kq nj kr nk kt nl ku nm nn ga\" data-selectable-paragraph=\"\">Building a model in TensorFlow<\/h1>\n<p id=\"45f0\" class=\"pw-post-body-paragraph lm ln iy bm b lo no ki lq lr np kl lt lu nq lw lx ly nr ma mb mc ns me mf mg ir ga\" data-selectable-paragraph=\"\">TensorFlow is an open-source software library that allows developers to create and train neural networks. TensorFlow works by feeding data into a graph of nodes. The nodes then perform mathematical operations on the data and pass the results to the next node in the graph.<\/p>\n<\/div>\n\n\n\n<div class=\"o dx nt nu id nv\" role=\"separator\"><\/div>\n\n\n\n<div class=\"ir is it iu iv\">\n<blockquote class=\"oa\"><p id=\"a783\" class=\"ob oc iy bm od oe of og oh oi oj mg cn\" data-selectable-paragraph=\"\">The MLOps difference? Visibility, reproducibility, and collaboration.&nbsp;<a class=\"au ll\" href=\"https:\/\/go.comet.ml\/ebook-Building-Effective-ML-Teams.html\" target=\"_blank\" rel=\"noopener ugc nofollow\">Learn more about building effective ML teams with our free ebook<\/a>.<\/p><\/blockquote>\n<\/div>\n\n\n\n<div class=\"o dx nt nu id nv\" role=\"separator\"><\/div>\n\n\n\n<div class=\"ir is it iu iv\">\n<p id=\"9055\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">To make TensorFlow work with Comet, you need to configure Comet to log the TensorFlow objects automatically. You can create a file, named&nbsp;<code class=\"fp ok ol om on b\">.comet.config<\/code>, and place it in the same directory as of your main script. The&nbsp;<code class=\"fp ok ol om on b\">.comet.config<\/code>&nbsp;file should contain the following configuration parameters:<\/p>\n<pre class=\"kx ky kz la gx oo bs op oq dz on\"><span id=\"4424\" class=\"ga or mx iy on b dm os ot l ou ov\" data-selectable-paragraph=\"\">[comet]\napi_key=YOUR_API_KEY\nproject_name=YOUR_PROJECT\nworkspace=YOUR_WORKSPACE<\/span><span id=\"6094\" class=\"ga or mx iy on b dm ow ot l ou ov\" data-selectable-paragraph=\"\">[comet_auto_log]\ngraph=True\nhistogram_weights=True\nhistogram_gradients=True\nhistogram_activations=True<\/span><\/pre>\n<p id=\"ddcf\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">In the comet_auto_log section, you should include all the elements that you want to log automatically in Comet. In the example above, we log graphs and three types of histograms.<\/p>\n<p id=\"cc5d\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Now we can start writing the code for our model. Firstly, we import the Comet library and then TensorFlow:<\/p>\n<pre class=\"kx ky kz la gx oo bs op oq dz on\"><span id=\"7fdd\" class=\"ga or mx iy on b dm os ot l ou ov\" data-selectable-paragraph=\"\">from comet_ml import Experiment\nimport tensorflow as tf<\/span><\/pre>\n<p id=\"77c3\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Then, we load the dataset. As an example, we use the&nbsp;<a class=\"au ll\" href=\"https:\/\/www.kaggle.com\/code\/prasadperera\/the-boston-housing-dataset\" target=\"_blank\" rel=\"noopener ugc nofollow\">Boston Housing dataset<\/a>, available in the list of toy datasets provided by Keras:<\/p>\n<pre class=\"kx ky kz la gx oo bs op oq dz on\"><span id=\"17de\" class=\"ga or mx iy on b dm os ot l ou ov\" data-selectable-paragraph=\"\">from tensorflow import keras\nfrom keras.datasets import boston_housing<\/span><span id=\"ad59\" class=\"ga or mx iy on b dm ow ot l ou ov\" data-selectable-paragraph=\"\">(train_data, train_targets), (test_data, test_targets) = boston_housing.load_data()<\/span><\/pre>\n<p id=\"3924\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Now, we build the TensorFlow model for a regression task:<\/p>\n<pre class=\"kx ky kz la gx oo bs op oq dz on\"><span id=\"3323\" class=\"ga or mx iy on b dm os ot l ou ov\" data-selectable-paragraph=\"\">model = keras.models.Sequential([\n  keras.layers.Flatten(),\n  keras.layers.Dense(16, activation='relu'),\n  keras.layers.Dense(5, activation='softmax')\n])<\/span><\/pre>\n<p id=\"cc24\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">We compile the model:<\/p>\n<pre class=\"kx ky kz la gx oo bs op oq dz on\"><span id=\"49c7\" class=\"ga or mx iy on b dm os ot l ou ov\" data-selectable-paragraph=\"\">model.compile(\n  optimizer='adam',\n  loss='mse',\n  metrics=['mae']\n)<\/span><\/pre>\n<p id=\"77d7\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">and we fit the model:<\/p>\n<pre class=\"kx ky kz la gx oo bs op oq dz on\"><span id=\"e4f0\" class=\"ga or mx iy on b dm os ot l ou ov\" data-selectable-paragraph=\"\">model.fit(\n   train_data,\n   train_targets,\u00c5\u03a9\n   epochs=8,\n   validation_data=(test_data, test_targets),\n)<\/span><\/pre>\n<p id=\"6bc2\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Please note that if you are writing your code in a notebook,&nbsp;<em class=\"ox\">you need to terminate the experiment<\/em>:<\/p>\n<pre class=\"kx ky kz la gx oo bs op oq dz on\"><span id=\"148b\" class=\"ga or mx iy on b dm os ot l ou ov\" data-selectable-paragraph=\"\">experiment.end()<\/span><\/pre>\n<h1 id=\"b5fe\" class=\"mw mx iy bm my mz na nb nc nd ne nf ng kn nh ko ni kq nj kr nk kt nl ku nm nn ga\" data-selectable-paragraph=\"\">Showing results in Comet<\/h1>\n<p id=\"3f2c\" class=\"pw-post-body-paragraph lm ln iy bm b lo no ki lq lr np kl lt lu nq lw lx ly nr ma mb mc ns me mf mg ir ga\" data-selectable-paragraph=\"\">Once the experiment is complete, you can see the results in Comet.<\/p>\n<p id=\"577c\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Under the&nbsp;<strong class=\"bm mh\">Charts<\/strong>&nbsp;menu, you can see the produced graphs:<\/p>\n<figure class=\"kx ky kz la gx lb gl gm paragraph-image\">\n<div class=\"lc ld do le ce lf\" tabindex=\"0\" role=\"button\">\n<figure><img loading=\"lazy\" decoding=\"async\" class=\"ce lg lh c aligncenter\" role=\"presentation\" src=\"https:\/\/miro.medium.com\/max\/700\/1*vm4uWSUZiosFaM_8JU5UKg.png\" alt=\"\" width=\"700\" height=\"320\"><\/figure><div class=\"gl gm oy\" style=\"text-align: center;\"><picture><source srcset=\"https:\/\/miro.medium.com\/max\/640\/1*vm4uWSUZiosFaM_8JU5UKg.png 640w, https:\/\/miro.medium.com\/max\/720\/1*vm4uWSUZiosFaM_8JU5UKg.png 720w, https:\/\/miro.medium.com\/max\/750\/1*vm4uWSUZiosFaM_8JU5UKg.png 750w, https:\/\/miro.medium.com\/max\/786\/1*vm4uWSUZiosFaM_8JU5UKg.png 786w, https:\/\/miro.medium.com\/max\/828\/1*vm4uWSUZiosFaM_8JU5UKg.png 828w, https:\/\/miro.medium.com\/max\/1100\/1*vm4uWSUZiosFaM_8JU5UKg.png 1100w, https:\/\/miro.medium.com\/max\/1400\/1*vm4uWSUZiosFaM_8JU5UKg.png 1400w\" sizes=\"(min-resolution: 4dppx) and (max-width: 700px) 50vw, (-webkit-min-device-pixel-ratio: 4) and (max-width: 700px) 50vw, (min-resolution: 3dppx) and (max-width: 700px) 67vw, (-webkit-min-device-pixel-ratio: 3) and (max-width: 700px) 65vw, (min-resolution: 2.5dppx) and (max-width: 700px) 80vw, (-webkit-min-device-pixel-ratio: 2.5) and (max-width: 700px) 80vw, (min-resolution: 2dppx) and (max-width: 700px) 100vw, (-webkit-min-device-pixel-ratio: 2) and (max-width: 700px) 100vw, 700px\" data-testid=\"og\">Image by Author<\/picture><\/div>\n<\/div>\n<\/figure>\n<p id=\"9743\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Produced graphs include:<\/p>\n<ul class=\"\">\n<li id=\"25b4\" class=\"mi mj iy bm b lo lp lr ls lu mk ly ml mc mm mg mn mo mp mq ga\" data-selectable-paragraph=\"\">Batch MAE and batch loss<\/li>\n<li id=\"937e\" class=\"mi mj iy bm b lo mr lr ms lu mt ly mu mc mv mg mn mo mp mq ga\" data-selectable-paragraph=\"\">Epoch duration<\/li>\n<li id=\"43c0\" class=\"mi mj iy bm b lo mr lr ms lu mt ly mu mc mv mg mn mo mp mq ga\" data-selectable-paragraph=\"\">Loss<\/li>\n<li id=\"e9e8\" class=\"mi mj iy bm b lo mr lr ms lu mt ly mu mc mv mg mn mo mp mq ga\" data-selectable-paragraph=\"\">MAE<\/li>\n<li id=\"0835\" class=\"mi mj iy bm b lo mr lr ms lu mt ly mu mc mv mg mn mo mp mq ga\" data-selectable-paragraph=\"\">Validation loss and validation batch loss<\/li>\n<li id=\"ceda\" class=\"mi mj iy bm b lo mr lr ms lu mt ly mu mc mv mg mn mo mp mq ga\" data-selectable-paragraph=\"\">Validation MAE and validation batch MAE<\/li>\n<\/ul>\n<p id=\"b13a\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Under the \u201cHistograms\u201d section, you can find the logged histograms:<\/p>\n<figure class=\"kx ky kz la gx lb gl gm paragraph-image\">\n<div class=\"lc ld do le ce lf\" tabindex=\"0\" role=\"button\">\n<figure><img loading=\"lazy\" decoding=\"async\" class=\"ce lg lh c aligncenter\" role=\"presentation\" src=\"https:\/\/miro.medium.com\/max\/700\/1*W8W1GVRflI1CYxRuq18-GQ.png\" alt=\"\" width=\"700\" height=\"337\"><\/figure><div class=\"gl gm oz\" style=\"text-align: center;\"><picture><source srcset=\"https:\/\/miro.medium.com\/max\/640\/1*W8W1GVRflI1CYxRuq18-GQ.png 640w, https:\/\/miro.medium.com\/max\/720\/1*W8W1GVRflI1CYxRuq18-GQ.png 720w, https:\/\/miro.medium.com\/max\/750\/1*W8W1GVRflI1CYxRuq18-GQ.png 750w, https:\/\/miro.medium.com\/max\/786\/1*W8W1GVRflI1CYxRuq18-GQ.png 786w, https:\/\/miro.medium.com\/max\/828\/1*W8W1GVRflI1CYxRuq18-GQ.png 828w, https:\/\/miro.medium.com\/max\/1100\/1*W8W1GVRflI1CYxRuq18-GQ.png 1100w, https:\/\/miro.medium.com\/max\/1400\/1*W8W1GVRflI1CYxRuq18-GQ.png 1400w\" sizes=\"(min-resolution: 4dppx) and (max-width: 700px) 50vw, (-webkit-min-device-pixel-ratio: 4) and (max-width: 700px) 50vw, (min-resolution: 3dppx) and (max-width: 700px) 67vw, (-webkit-min-device-pixel-ratio: 3) and (max-width: 700px) 65vw, (min-resolution: 2.5dppx) and (max-width: 700px) 80vw, (-webkit-min-device-pixel-ratio: 2.5) and (max-width: 700px) 80vw, (min-resolution: 2dppx) and (max-width: 700px) 100vw, (-webkit-min-device-pixel-ratio: 2) and (max-width: 700px) 100vw, 700px\" data-testid=\"og\">Image by Author<\/picture><\/div>\n<\/div>\n<\/figure>\n<p id=\"0fb4\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">You can see the results of the full experiment at&nbsp;<a class=\"au ll\" href=\"https:\/\/www.comet.com\/alod83\/comet-tensorflow\" target=\"_blank\" rel=\"noopener ugc nofollow\">this link<\/a>.<\/p>\n<h1 id=\"a2a3\" class=\"mw mx iy bm my mz na nb nc nd ne nf ng kn nh ko ni kq nj kr nk kt nl ku nm nn ga\" data-selectable-paragraph=\"\">Summary<\/h1>\n<p id=\"7abb\" class=\"pw-post-body-paragraph lm ln iy bm b lo no ki lq lr np kl lt lu nq lw lx ly nr ma mb mc ns me mf mg ir ga\" data-selectable-paragraph=\"\">Congratulations! You have just tracked your TensorFlow model in Comet!<\/p>\n<p id=\"1267\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Integrating TensorFlow with Comet is a great way to streamline the process of monitoring and logging your experiments. By using Comet, you can easily compare the performance of different configurations and see which ones perform better. In addition, Comet makes it easy to share your results with others.<\/p>\n<p id=\"beb2\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">You can read more information on how to integrate Comet with TensorFlow in the Comet official documentation available at&nbsp;<a class=\"au ll\" href=\"https:\/\/www.comet.com\/docs\/python-sdk\/tensorflow-model-analysis\/\" target=\"_blank\" rel=\"noopener ugc nofollow\">this link<\/a>.<\/p>\n<p id=\"5cb5\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">The code of the example described in this article is available at&nbsp;<a class=\"au ll\" href=\"https:\/\/colab.research.google.com\/drive\/1eE6p3nYXkRaJAdAkHWHipErf9VGv2mQF#scrollTo=R2FWNl4LUm4C\" target=\"_blank\" rel=\"noopener ugc nofollow\">this link<\/a>.<\/p>\n<p id=\"c1ff\" class=\"pw-post-body-paragraph lm ln iy bm b lo lp ki lq lr ls kl lt lu lv lw lx ly lz ma mb mc md me mf mg ir ga\" data-selectable-paragraph=\"\">Happy coding! Happy&nbsp;<a class=\"au ll\" href=\"https:\/\/www.comet.com\/\" target=\"_blank\" rel=\"noopener ugc nofollow\">Comet<\/a>!<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Photo by&nbsp;Alex Knight&nbsp;on&nbsp;Unsplash Neural Networks are a subset of artificial intelligence, aiming at modeling the human brain through mathematical concepts. A neural network is composed of a series of interconnected nodes, or neurons, that process information. Nodes are organized in more or less complicated layers. Neural networks can be used for a variety of tasks, [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"customer_name":"","customer_description":"","customer_industry":"","customer_technologies":"","customer_logo":"","footnotes":""},"categories":[5,9],"tags":[],"coauthors":[132],"class_list":["post-4574","post","type-post","status-publish","format-standard","hentry","category-partners-integrations","category-product"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Using TensorFlow in Comet - Comet<\/title>\n<meta name=\"description\" content=\"Neural Networks are a subset of artificial intelligence, aiming at modeling the human brain through mathematical concepts.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Using TensorFlow in Comet\" \/>\n<meta property=\"og:description\" content=\"Neural Networks are a subset of artificial intelligence, aiming at modeling the human brain through mathematical concepts.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/\" \/>\n<meta property=\"og:site_name\" content=\"Comet\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/cometdotml\" \/>\n<meta property=\"article:published_time\" content=\"2022-11-11T01:50:44+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-04-24T17:16:29+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/miro.medium.com\/max\/700\/0*Lhfv0VDUl01absF3\" \/>\n<meta name=\"author\" content=\"Angelica Lo Duca\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@Cometml\" \/>\n<meta name=\"twitter:site\" content=\"@Cometml\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Angelica Lo Duca\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Using TensorFlow in Comet - Comet","description":"Neural Networks are a subset of artificial intelligence, aiming at modeling the human brain through mathematical concepts.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/","og_locale":"en_US","og_type":"article","og_title":"Using TensorFlow in Comet","og_description":"Neural Networks are a subset of artificial intelligence, aiming at modeling the human brain through mathematical concepts.","og_url":"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/","og_site_name":"Comet","article_publisher":"https:\/\/www.facebook.com\/cometdotml","article_published_time":"2022-11-11T01:50:44+00:00","article_modified_time":"2025-04-24T17:16:29+00:00","og_image":[{"url":"https:\/\/miro.medium.com\/max\/700\/0*Lhfv0VDUl01absF3","type":"","width":"","height":""}],"author":"Angelica Lo Duca","twitter_card":"summary_large_image","twitter_creator":"@Cometml","twitter_site":"@Cometml","twitter_misc":{"Written by":"Angelica Lo Duca","Est. reading time":"4 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/#article","isPartOf":{"@id":"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/"},"author":{"name":"Team Comet Digital","@id":"https:\/\/www.comet.com\/site\/#\/schema\/person\/6266601170c60a7a82b3e0043fbe8ddf"},"headline":"Using TensorFlow in Comet","datePublished":"2022-11-11T01:50:44+00:00","dateModified":"2025-04-24T17:16:29+00:00","mainEntityOfPage":{"@id":"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/"},"wordCount":657,"publisher":{"@id":"https:\/\/www.comet.com\/site\/#organization"},"image":{"@id":"https:\/\/www.comet.com\/site\/blog\/using-tensorflow-in-comet\/#primaryimage"},"thumbnailUrl":"https:\/\/miro.medium.com\/max\/700\/0*Lhfv0VDUl01absF3","articleSection":["Partners &amp; 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