{"id":24001,"date":"2018-08-08T03:30:27","date_gmt":"2018-08-08T03:30:27","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=24001"},"modified":"2026-04-28T10:46:57","modified_gmt":"2026-04-28T05:16:57","slug":"applications-of-machine-learning","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/applications-of-machine-learning\/","title":{"rendered":"17 Top Applications of Machine Learning with Python"},"content":{"rendered":"<div class='__iawmlf-post-loop-links' style='display:none;' data-iawmlf-post-links='[{&quot;id&quot;:1418,&quot;href&quot;:&quot;https:\\\/\\\/en.wikipedia.org\\\/wiki\\\/Machine_learning&quot;,&quot;archived_href&quot;:&quot;http:\\\/\\\/web-wp.archive.org\\\/web\\\/20251130072921\\\/https:\\\/\\\/en.wikipedia.org\\\/wiki\\\/Machine_learning&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[{&quot;date&quot;:&quot;2025-12-09 06:41:40&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2025-12-12 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02:25:23&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-04-17 05:49:08&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-04-20 06:38:49&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-04-23 08:15:10&quot;,&quot;http_code&quot;:404},{&quot;date&quot;:&quot;2026-04-26 10:02:48&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-04-29 14:13:55&quot;,&quot;http_code&quot;:429},{&quot;date&quot;:&quot;2026-05-02 19:39:01&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-06 04:50:24&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-09 06:14:41&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-12 08:20:37&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-15 09:29:22&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-18 11:00:28&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-21 13:05:16&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-24 13:13:21&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-27 13:51:19&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-30 15:11:03&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-02 18:48:44&quot;,&quot;http_code&quot;:404},{&quot;date&quot;:&quot;2026-06-06 01:41:18&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-09 05:37:43&quot;,&quot;http_code&quot;:404},{&quot;date&quot;:&quot;2026-06-12 11:02:59&quot;,&quot;http_code&quot;:200}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-06-12 11:02:59&quot;,&quot;http_code&quot;:200},&quot;process&quot;:&quot;done&quot;}]'><\/div>\n<p>In our last tutorial, we discussed <a href=\"https:\/\/data-flair.training\/blogs\/python-machine-learning-techniques\/\"><strong>Machine learning Techniques with<\/strong> <strong>Python<\/strong><\/a>. Today, we dedicate this <strong><a href=\"https:\/\/data-flair.training\/blogs\/python-machine-learning-tutorial\/\">Python Machine Learning tutorial <\/a><\/strong>to learning about the applications of Machine Learning with Python Programming. Let\u2019s take a look at the areas where machines are used in the industry.<\/p>\n<p>Machine Learning has revolutionised several fields by eradicating the need for manual intervention and introducing a remarkable intuitive idea. It helps in forecasting outcomes in various sectors like healthcare and individualises the processes of patient care.<\/p>\n<p>Likewise, in the finance field, the ML algorithms are trained to identify market patterns to assist in investment and flag any fraud. The dynamism of ML is a big plus as it accommodates change and can offer uniqueness in various domains, making it an essential part of modern technology.<\/p>\n<p>So, start the Applications of Machine Learning with Python.<\/p>\n<div id=\"attachment_24037\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-ML-with-Python-01.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24037\" class=\"wp-image-24037 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-ML-with-Python-01.jpg\" alt=\"17 Top Applications of Machine Learning with Python\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-ML-with-Python-01.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-ML-with-Python-01-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-ML-with-Python-01-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-ML-with-Python-01-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-ML-with-Python-01-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-24037\" class=\"wp-caption-text\">17 Top Applications of Machine Learning with Python<\/p><\/div>\n<h3 class=\"western\">Why is Python used for Machine Learning?<\/h3>\n<p>Before we proceed to the applications of Machine Learning with Python, you\u2019re probably asking yourself- why Python? Among tools like <strong><a href=\"https:\/\/data-flair.training\/blogs\/r-programming-tutorial\/\">R programming<\/a><\/strong> and <strong><a href=\"https:\/\/data-flair.training\/blogs\/sas-tutorial\/\">SAS<\/a><\/strong>, here\u2019s why we\u2019ll go with Python Programming Language-<br \/>\n<strong><a href=\"https:\/\/data-flair.training\/blogs\/machine-learning-tutorial\/\">Follow this link to know about Machine Learning<\/a><\/strong><\/p>\n<h4 class=\"western\">a. Simple<\/h4>\n<p>The sole <strong><a href=\"https:\/\/data-flair.training\/blogs\/reasons-why-should-i-learn-python\/\">reason why Python<\/a><\/strong> is often chosen as an introductory language to programming is its simplicity. It is simple, yet powerful. Python is easy to write and simple to understand. This behaviour of its makes it intuitive. Situations like getting your code from another developer who uses third-party components mean you need very little cognitive overhead. It is also true that code is read more often than it is written. Therefore, simplicity serves to be a great asset to Python.<\/p>\n<h4 class=\"western\">b. Huge Set of Relevant Libraries<\/h4>\n<p>Python has a wide collection of libraries for machine learning purposes. These include <a href=\"https:\/\/data-flair.training\/blogs\/python-numpy-tutorial\/\"><strong>Python NumPy<\/strong><\/a>, <strong><a href=\"https:\/\/data-flair.training\/blogs\/scipy-tutorial\/\">SciPy<\/a><\/strong>, scikit-learn, and many more. These are good for all intrinsic tasks of machine learning.<\/p>\n<ul>\n<li><strong>scikit-learn:<\/strong>\u00a0Good for data mining, data analysis, and machine learning.<\/li>\n<li><strong>pylearn2:<\/strong>\u00a0More flexible than scikit-learn.<\/li>\n<li><strong>PyBrain:<\/strong>\u00a0Modular ML library with flexible, easy, and powerful ML algorithms and predefined environments to test and compare algorithms.<\/li>\n<li><strong>Orange:<\/strong>\u00a0Open-source data visualisation and analysis, has components for machine learning, has extensions for biometrics and text mining, has features for data analytics, supports data mining through visual programming or Python scripting.<\/li>\n<li><strong>PyML:<\/strong>\u00a0The Interactive object-oriented framework for machine learning, written in Python.<\/li>\n<li><strong>Milk:<\/strong>\u00a0Machine learning toolkit, has SVMs, k-NN, random forests, decision trees, and performs feature selection.<\/li>\n<li><strong>Shogun:<\/strong>\u00a0Machine learning toolbox, focuses on large-scale kernel methods and SVMs.<\/li>\n<li><strong>TensorFlow:<\/strong>\u00a0High-level <strong><a href=\"https:\/\/data-flair.training\/blogs\/tensorflow-recurrent-neural-network\/\">Neural Network <\/a><\/strong>Library.<\/li>\n<\/ul>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/tensorflow-tutorial\/\" target=\"_blank\" rel=\"noopener\">Follow this link to know about the TensorFlow Tutorial<\/a><\/strong><\/p>\n<h3>Applications of Machine Learning with Python<\/h3>\n<div id=\"attachment_24035\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-Machine-Learning-with-Python-01.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24035\" class=\"wp-image-24035 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-Machine-Learning-with-Python-01.jpg\" alt=\"17 Top Applications of Machine Learning with Python\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-Machine-Learning-with-Python-01.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-Machine-Learning-with-Python-01-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-Machine-Learning-with-Python-01-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-Machine-Learning-with-Python-01-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Applications-of-Machine-Learning-with-Python-01-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-24035\" class=\"wp-caption-text\">17 Top Applications of Machine Learning with Python<\/p><\/div>\n<h4 class=\"western\">1. Virtual Personal Assistants<\/h4>\n<p>Names like Siri and Alexa bring to mind the capabilities of virtual assistants. We can ask Siri to make a call for you or play music. You can request Alexa for today\u2019s weather forecast. You can even set an alarm or send an SMS. What makes this easier on you is that you only need to speak to it and it will listen to your command. This comes in handy for those differently abled. Such assistants take note of how you interact with them and use that to make your next experience with them better.<\/p>\n<div id=\"attachment_24018\" style=\"width: 665px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/siri.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24018\" class=\"wp-image-24018 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/siri.png\" alt=\"Applications of Machine Learning with Python\" width=\"655\" height=\"655\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/siri.png 655w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/siri-150x150.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/siri-300x300.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/siri-100x100.png 100w\" sizes=\"auto, (max-width: 655px) 100vw, 655px\" \/><\/a><p id=\"caption-attachment-24018\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4 class=\"western\">2. Social Media Services<\/h4>\n<p>By now, you would have noticed several features of Facebook- \u2018People You May Know\u2019 and \u2018Face Recognition\u2019. It uses machine learning to monitor your activity- what profiles you visit, which people to send requests to, which ones you accept requests from, the people you tag, among much more. With this, Facebook hopes to provide you with a richer experience on its platform so you will use it regularly.<\/p>\n<div id=\"attachment_24019\" style=\"width: 610px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/facebook.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24019\" class=\"wp-image-24019 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/facebook.png\" alt=\"Applications of Machine Learning with Python\" width=\"600\" height=\"600\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/facebook.png 600w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/facebook-150x150.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/facebook-300x300.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/facebook-100x100.png 100w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/a><p id=\"caption-attachment-24019\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/reasons-why-should-i-learn-python\/\">Do you know the Reasons Why Should we Learn Python<\/a><\/strong><\/p>\n<h4 class=\"western\">3. Online Customer Support<\/h4>\n<p>Websites like educators and shopping platforms will often pop up a live chat to help you with your questions. A visitor with a head full of questions is more likely to leave than stay and possibly make a purchase. Some websites use a chatbot instead to pull information to the website and try to address the customer\u2019s queries.<\/p>\n<div id=\"attachment_24020\" style=\"width: 453px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/chat.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24020\" class=\"wp-image-24020 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/chat.png\" alt=\"Applications of Machine Learning with Python\" width=\"443\" height=\"405\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/chat.png 443w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/chat-150x137.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/chat-300x274.png 300w\" sizes=\"auto, (max-width: 443px) 100vw, 443px\" \/><\/a><p id=\"caption-attachment-24020\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4 class=\"western\">4. Online Fraud Detection<\/h4>\n<p>If you\u2019re familiar with PayPal, you realise your trust in it. It uses machine learning to stand in defence against illegal acts like money laundering. By comparing millions of transactions, it can find out which ones are illegitimate. It detects and prevents threats, such as malware filtering.<\/p>\n<div id=\"attachment_24021\" style=\"width: 402px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/fraud.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24021\" class=\"wp-image-24021 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/fraud.jpg\" alt=\"Applications of Machine Learning with Python\" width=\"392\" height=\"252\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/fraud.jpg 392w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/fraud-150x96.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/fraud-300x193.jpg 300w\" sizes=\"auto, (max-width: 392px) 100vw, 392px\" \/><\/a><p id=\"caption-attachment-24021\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4 class=\"western\">5. Product Recommendations<\/h4>\n<p>Shopping platforms like Amazon and Jabong notice what products you look at and suggest similar products to you. If this gets a favourite product across to you and results in a purchase you make with them, it\u2019s a win for them. For this, it also uses your wishlist and cart contents.<\/p>\n<p>Machine Learning is used to recommend products or services based on users&#8217; purchase history.<\/p>\n<div id=\"attachment_24022\" style=\"width: 1375px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recommendations.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24022\" class=\"wp-image-24022 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recommendations.png\" alt=\"Applications of Machine Learning with Python\" width=\"1365\" height=\"531\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recommendations.png 1365w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recommendations-150x58.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recommendations-300x117.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recommendations-768x299.png 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recommendations-1024x398.png 1024w\" sizes=\"auto, (max-width: 1365px) 100vw, 1365px\" \/><\/a><p id=\"caption-attachment-24022\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/python-functions\/\">Read about Python Functions with Syntax and Examples<\/a><\/strong><\/p>\n<h4 class=\"western\">6. Refining Search Engine Results<\/h4>\n<p>The searches you make in search engines like Google monitor your response. Do you visit a top listing and stick around for a while? Do you get to the third page and leave without clicking any link? Google makes note of the findings and aims to improve your search next time.<\/p>\n<div id=\"attachment_24023\" style=\"width: 1378px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/google.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24023\" class=\"wp-image-24023 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/google.png\" alt=\"Applications of Machine Learning with Python\" width=\"1368\" height=\"469\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/google.png 1368w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/google-150x51.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/google-300x103.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/google-768x263.png 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/google-1024x351.png 1024w\" sizes=\"auto, (max-width: 1368px) 100vw, 1368px\" \/><\/a><p id=\"caption-attachment-24023\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4>7. Fighting Web Spam<\/h4>\n<p>Many email clients use rule-based spam filtering. Spammers develop new tricks to get around this. So, clients like Gmail use machine learning to keep their spam filters updated. This is also a problem with Google search results and other search engines. Common spam-filtering techniques are Multi-Layer Perceptron and C 4.5 Decision Tree Induction.<\/p>\n<div id=\"attachment_24024\" style=\"width: 720px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/spam.gif\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24024\" class=\"wp-image-24024 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/spam.gif\" alt=\"Applications of Machine Learning with Python\" width=\"710\" height=\"236\" \/><\/a><p id=\"caption-attachment-24024\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4>8. Automatic Translation<\/h4>\n<p>Machine Learning lets us translate text into another language. The ML algorithm for these figures shows how words fit together and then uses this information to improve the quality of a translation. With this, we can also translate the text on images using neural networks to identify letters.<\/p>\n<div id=\"attachment_24025\" style=\"width: 310px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/translation.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24025\" class=\"wp-image-24025 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/translation.png\" alt=\"Applications of Machine Learning with Python\" width=\"300\" height=\"219\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/translation.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/translation-150x110.png 150w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><p id=\"caption-attachment-24025\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/python-pyqt5-tutorial\/\" target=\"_blank\" rel=\"noopener\">Let&#8217;s Explore Python PyQt5 Tutorial<\/a><\/strong><\/p>\n<h4 class=\"western\">9. Video Surveillance<\/h4>\n<p>Some crimes can be avoided by sensing them way before they can happen. Behaviour, like standing motionless, napping on a bench, and following another individual, can alert human attendants via a video surveillance system.<\/p>\n<div id=\"attachment_24026\" style=\"width: 835px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/surveillance.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24026\" class=\"wp-image-24026 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/surveillance.png\" alt=\"Applications of Machine Learning with Python\" width=\"825\" height=\"510\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/surveillance.png 825w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/surveillance-150x93.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/surveillance-300x185.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/surveillance-768x475.png 768w\" sizes=\"auto, (max-width: 825px) 100vw, 825px\" \/><\/a><p id=\"caption-attachment-24026\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4 class=\"western\">10. Predicting Music Choices<\/h4>\n<p>Products like Genius by Apple Music monitor what you listen to. Later, it can suggest a list of songs you are likely to prefer. It also picks songs from your playlist to create libraries that sound good together.<\/p>\n<div id=\"attachment_24027\" style=\"width: 264px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Genius.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24027\" class=\"wp-image-24027 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Genius.png\" alt=\"Applications of Machine Learning with Python\" width=\"254\" height=\"291\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Genius.png 254w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Genius-131x150.png 131w\" sizes=\"auto, (max-width: 254px) 100vw, 254px\" \/><\/a><p id=\"caption-attachment-24027\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4 class=\"western\">11. Drug Discovery and Disease Diagnosis<\/h4>\n<p>With<a href=\"https:\/\/data-flair.training\/blogs\/machine-learning-algorithm\/\"><strong> ML algorithms<\/strong><\/a>, we can perform the following tasks-<\/p>\n<div id=\"attachment_24028\" style=\"width: 499px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/drug-discovery.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24028\" class=\"wp-image-24028 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/drug-discovery.png\" alt=\"Applications of Machine Learning with Python\" width=\"489\" height=\"446\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/drug-discovery.png 489w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/drug-discovery-150x137.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/drug-discovery-300x274.png 300w\" sizes=\"auto, (max-width: 489px) 100vw, 489px\" \/><\/a><p id=\"caption-attachment-24028\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<ul>\n<li>Initial screening of drug compounds.<\/li>\n<li>Predicting success rate based on biological factors.<\/li>\n<li>R&amp;D technologies like Next-Generation Sequencing.<\/li>\n<li>Understand disease processes.<\/li>\n<li>Design effective treatments for diseases.<\/li>\n<li>Personalising drug combinations.<\/li>\n<li>Produce cheaper drugs with improved replication.<\/li>\n<li>Research and develop diagnostics and treatments.<\/li>\n<li>It analyses patients&#8217; records to assist with disease detection and personalise treatments.<\/li>\n<\/ul>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/python-statistics\/\" target=\"_blank\" rel=\"noopener\">Read about Python Statistics &#8211; p-Value, Correlation, T-test, KS Test<\/a><\/strong><\/p>\n<h4 class=\"western\">12. Face Recognition<\/h4>\n<p>Facilities like face detection are often something we see with Facebook. When we want to tag a photo, Facebook automatically suggests a few names to us. Most of the time, the first name is accurate for the face it has detected. This has machine learning to credit.<\/p>\n<div id=\"attachment_24029\" style=\"width: 522px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recognizing-faces.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24029\" class=\"wp-image-24029 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recognizing-faces.png\" alt=\"Applications of Machine Learning with Python\" width=\"512\" height=\"494\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recognizing-faces.png 512w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recognizing-faces-150x145.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/recognizing-faces-300x289.png 300w\" sizes=\"auto, (max-width: 512px) 100vw, 512px\" \/><\/a><p id=\"caption-attachment-24029\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<h4 class=\"western\">13. Pricing Insurance Plans<\/h4>\n<p>Machine Learning can detect if a driver is likely to cause a large-loss case during the term of insurance. This lets insurance firms price insurance plans accordingly.<\/p>\n<h4 class=\"western\">14. Autonomous, Self-Driving Cars<\/h4>\n<p>These cars receive data on nearby objects and their sizes and speeds via sensors. Based on how they behave, it categorises objects as cyclists, pedestrians, and other cars, among others. It uses this data to compare stored maps to current conditions. Such cars make use of Machine Vision algorithms.<\/p>\n<div id=\"attachment_24030\" style=\"width: 533px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/self-driving-car.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-24030\" class=\"wp-image-24030 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/self-driving-car.png\" alt=\"Applications of Machine Learning with Python\" width=\"523\" height=\"243\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/self-driving-car.png 523w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/self-driving-car-150x70.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/self-driving-car-300x139.png 300w\" sizes=\"auto, (max-width: 523px) 100vw, 523px\" \/><\/a><p id=\"caption-attachment-24030\" class=\"wp-caption-text\">Applications of Machine Learning with Python<\/p><\/div>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/python-data-science-environment-setup\/\">Do you know the Python Data Science Environment Setup<\/a><\/strong><\/p>\n<h3>More Machine Learning Applications<\/h3>\n<p>Other than what we just mentioned, we can use Machine Learning for the following purposes-<\/p>\n<ul>\n<li>Identifying human genes that predispose people to cancer.<\/li>\n<li>Identifying what consumers respond to.<\/li>\n<li>Trading stocks and derivatives.<\/li>\n<li>Packet inspection for anti-virus software.<\/li>\n<li>Delayed aeroplane flights.<\/li>\n<li>Factory maintenance diagnostics.<\/li>\n<li>Behavioural advertisement for products.<\/li>\n<li>Natural language processing (NLP) is used in Siri and Alexa.<\/li>\n<li>Computer vision uses facial recognition for security.<\/li>\n<li>Email management manages spam detection and malware filtering.<\/li>\n<li>Automation through intelligent chatbots makes solving user queries easier.<\/li>\n<\/ul>\n<p>So, this was all about\u00a0Applications of Machine Learning with Python. Hope you like our explanation.<\/p>\n<h3 class=\"western\">Conclusion<\/h3>\n<p>Hence, we conclude our tutorial on applications of machine learning with Python. Got more to add? Feel free to drop it in the comments below.<br \/>\n<strong>Related Topic-<\/strong><\/p>\n<p><strong><a href=\"https:\/\/data-flair.training\/blogs\/python-machine-learning-techniques\/\" target=\"_blank\" rel=\"noopener\">Machine Learning Techniques<\/a><\/strong><br \/>\n<strong><a href=\"https:\/\/en.wikipedia.org\/wiki\/Machine_learning\">For reference<\/a><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In our last tutorial, we discussed Machine learning Techniques with Python. Today, we dedicate this Python Machine Learning tutorial to learning about the applications of Machine Learning with Python Programming. 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