
{"id":27387,"date":"2023-07-25T13:31:41","date_gmt":"2023-07-25T11:31:41","guid":{"rendered":"https:\/\/careerfoundry.inbearbeitung.de\/en\/?p=27387"},"modified":"2023-12-13T12:50:21","modified_gmt":"2023-12-13T11:50:21","slug":"what-is-machine-learning","status":"publish","type":"post","link":"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-is-machine-learning\/","title":{"rendered":"What is Machine Learning? A Complete Beginner\u2019s Guide"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Are you curious about machine learning (ML) and what it can do for you? Have you ever tried to learn about this cutting-edge technology only to find yourself lost between buzzwords and technical jargon?<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Don&#8217;t worry; this guide is here to help anyone understand the basics of ML\u2014including complete beginners!<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We\u2019ll cover all the essentials you&#8217;ll need to know, from defining what is machine learning, exploring its tools, looking at ethical considerations, and discovering what machine learning engineers do<\/span><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you&#8217;d like to skip to a certain section, just use the clickable menu:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"#what-is-machine-learning\"><span style=\"font-weight: 400;\">What is machine learning?<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"#how-does-machine-learning-work\"><span style=\"font-weight: 400;\">How does machine learning work?<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"#machine-learning-examples\"><span style=\"font-weight: 400;\">Machine learning examples<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"#ethical-considerations-of-machine-learning\"><span style=\"font-weight: 400;\">Ethical considerations of machine learning<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"#the-role-of-the-machine-learning-engineer\"><span style=\"font-weight: 400;\">The role of the machine learning engineer<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"#final-thoughts\"><span style=\"font-weight: 400;\">Final thoughts<\/span><\/a><\/li>\n<li><a href=\"#machine-learning-faqs\"><span style=\"font-weight: 400;\">Machine learning FAQ<\/span><\/a><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">So if you&#8217;re ready, let&#8217;s dive in and have your first look at ML.<\/span><\/p>\n<h2 id=\"what-is-machine-learning\">1. What is machine learning?<\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning is a type of artificial intelligence (AI) that allows computer programs to learn from data and experiences without being explicitly programmed.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">At its core, machine learning is the process of using algorithms to analyze data. It allows computers to &#8220;learn&#8221; from that data without being explicitly programmed or told what to do by a human operator.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Instead, ML uses statistical techniques to make sense of large datasets, identify patterns in them, and make predictions about future outcomes.<\/span><\/p>\n<p>If you&#8217;d prefer to learn more visually, then check out this video we made explaining what machine learning is:<\/p>\n<style>.embed-container { position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden; max-width: 100%; } .embed-container iframe, .embed-container object, .embed-container embed { position: absolute; top: 0; left: 0; width: 100%; height: 100%; }<\/style>\n<div class=\"embed-container\"><iframe src=\"https:\/\/www.youtube.com\/embed\/\/i4vKOCMgdgc\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/div>\n<p>So, now that you know what is machine learning, it&#8217;s time to examine closer how it functions.<\/p>\n<h2 id=\"how-does-machine-learning-work\">2. How does machine learning work?<\/h2>\n<p><span style=\"font-weight: 400;\">At its simplest, machine learning works by feeding data into an algorithm that can identify patterns in the data and make predictions. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is made possible through some key components that make up this machine-learning process. These<\/span><span style=\"font-weight: 400;\"> vital components of ML are:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Data<\/b><span style=\"font-weight: 400;\">: This is used to train the ML algorithm so it can identify patterns and make predictions. It can be structured or unstructured, depending on how it&#8217;s being used.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Algorithms<\/b><span style=\"font-weight: 400;\">: This is the set of instructions that ML uses to analyze data and make predictions.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Model<\/b><span style=\"font-weight: 400;\">: The model is the &#8220;brain&#8221; of the ML algorithm, which processes and stores information from the data to make decisions.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Training<\/b><span style=\"font-weight: 400;\">: This is how machine learning algorithms learn from data by being fed large amounts of it so they can identify patterns and relationships in it.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Inference<\/b><span style=\"font-weight: 400;\">: This is the process of using the ML algorithm to create a calculated output score.<\/span><\/li>\n<\/ol>\n<h3><span style=\"font-weight: 400;\">Machine learning tools\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">To carry out these tasks, some tools and technologies are needed. <\/span><span style=\"font-weight: 400;\">Here are some of the most<\/span>\u00a0<a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/machine-learning-tools\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">common tools used for machine learning<\/span><\/a><span style=\"font-weight: 400;\">:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Python<\/b><span style=\"font-weight: 400;\">: A popular programming language used to develop applications for ML projects.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>TensorFlow<\/b><span style=\"font-weight: 400;\">: An open-source library developed by Google that allows users to define, optimize, and execute models using data flow graphs.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Keras<\/b><span style=\"font-weight: 400;\">: A high-level neural network application programming interface (API) written in Python that allows users to define and train deep learning models rapidly.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Scikit-learn<\/b><span style=\"font-weight: 400;\">: A Python library for machine learning that specializes in data analysis, classification, and clustering algorithms.<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">These tools provide the basis for the machine learning engineer to develop applications and use them for a variety of tasks. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you&#8217;re interested in learning more about whether to learn Python or R or Java, check out our full guide to <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/best-machine-learning-languages\/\" target=\"_blank\" rel=\"noopener\">which languages are best for machine learning<\/a>.<\/span><\/p>\n<h2 id=\"machine-learning-examples\">3. Machine learning examples<\/h2>\n<p><span style=\"font-weight: 400;\">To better understand how ML works, let\u2019s look at some real-world examples:<\/span><\/p>\n<h3>1. Computer vision<\/h3>\n<p><span style=\"font-weight: 400;\">One example is computer vision, where an ML algorithm can be used to identify objects in images or videos. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is done by feeding large amounts of data into an algorithm that looks for patterns and then uses this information to label the objects correctly.<\/span><\/p>\n<h3>2. AI-driven chatbots<\/h3>\n<p><span style=\"font-weight: 400;\">Another application is AI-driven chatbots. These are computer programs designed to simulate a human conversation. They are trained using ML algorithms to respond to user queries and provide answers that mimic natural language.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, an advanced version of an AI chatbot is ChatGPT, which is a conversational chatbot trained on data through an advanced machine learning model called Reinforcement Learning from Human Feedback (RLHF).<\/span><\/p>\n<h3>3. Text analysis<\/h3>\n<p><span style=\"font-weight: 400;\">Text analysis is another example of ML in action. In this case, an algorithm can be used to analyze large amounts of text and identify trends or patterns in it. This could be useful for things like <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/sentiment-analysis\/\" target=\"_blank\" rel=\"noopener\">sentiment analysis<\/a> or <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/predictive-analytics\/\" target=\"_blank\" rel=\"noopener\">predictive analytics<\/a>.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This leverages <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-are-nlp-algorithms\/\" target=\"_blank\" rel=\"noopener\">Natural Language Processing (NLP)<\/a> to convert text into data that ML algorithms can then use.<\/span><\/p>\n<h2 id=\"ethical-considerations-of-machine-learning\">4. Ethical considerations of machine learning<\/h2>\n<p><span style=\"font-weight: 400;\">As with any technology, there are ethical considerations associated with machine learning. It&#8217;s important to consider the potential impact of ML when choosing to deploy it in your business or organization.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Some common considerations include:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Privacy and security<\/b><span style=\"font-weight: 400;\">: When collecting data for ML algorithms, it&#8217;s important to think about how this information will be protected and who will have access to it.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Bias and discrimination<\/b><span style=\"font-weight: 400;\">: If the data used to train an algorithm is biased in any way, then the results may also be biased. It&#8217;s important to ensure that all data is unbiased and representative of the population. <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/bias-in-machine-learning\/\" target=\"_blank\" rel=\"noopener\">Bias in machine learning<\/a> is a huge issue set to define the next decade of the field.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Human job displacement<\/b><span style=\"font-weight: 400;\">: Machine learning algorithms can be used to automate many tasks, so this brings about a new question on whether it impacts human employment opportunities.<\/span><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-27463\" src=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2023\/07\/machine-learning-engineers-are-in-high-demand.jpeg\" alt=\"A machine learning engineer sits at his laptop in an open office.\" width=\"1200\" height=\"600\" title=\"\" srcset=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2023\/07\/machine-learning-engineers-are-in-high-demand.jpeg 1200w, https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2023\/07\/machine-learning-engineers-are-in-high-demand-300x150.jpeg 300w, https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2023\/07\/machine-learning-engineers-are-in-high-demand-1024x512.jpeg 1024w, https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2023\/07\/machine-learning-engineers-are-in-high-demand-768x384.jpeg 768w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/p>\n<h2 id=\"the-role-of-the-machine-learning-engineer\">5. The role of the machine learning engineer<\/h2>\n<p><span style=\"font-weight: 400;\">So, now that you know what is machine learning, it&#8217;s time to look closer at some of the people responsible for using it. While there are quite a few <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/machine-learning-jobs\/\" target=\"_blank\" rel=\"noopener\">machine learning jobs<\/a> out there, an ML engineer is perhaps the main one.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A <\/span><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/machine-learning-engineer\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">machine learning engineer<\/span><\/a><span style=\"font-weight: 400;\"> is the person responsible for designing, developing, testing, and deploying ML models. They must be highly skilled in both software engineering and data science to be effective in this role.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Some common tasks of a machine learning engineer include:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Designing ML algorithms<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Developing software to implement those algorithms<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Testing and validating the accuracy of the algorithms<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Deploying ML models into production<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Maintaining and optimizing the ML algorithms<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">However, this job of <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/machine-learning-models\/\" target=\"_blank\" rel=\"noopener\">developing and maintaining machine learning models<\/a> isn&#8217;t limited to a ML engineer either. This expands to other similar roles in the data profession, such as data scientists, software engineers, and data analysts.<\/span><\/p>\n<h2 id=\"final-thoughts\">6. Final thoughts<\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning is definitely an exciting field, especially with all the new developments in the generative AI\/ML space.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To recap all the aspects covered in this article on what is machine learning, here are some key points:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Machine learning is a subset of AI and involves using algorithms to learn from data without being explicitly programmed.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Examples of ML applications include computer vision, chatbots, and text analysis.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ethical considerations should be taken into account when deploying ML models, such as privacy and security issues, bias in data, and potential job displacement due to automation.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The role of the machine learning engineer involves designing, developing, testing, and deploying ML models.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">It can be intimidating to start learning ML, but with the right resources and determination, you can get started on your journey.<\/span><\/p>\n<p>CareerFoundry&#8217;s <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/courses\/machine-learning-with-python\/\"><strong>Machine Learning with Python course<\/strong><\/a> is designed to be your one-stop shop for getting into this exciting area of data analytics. Possible as a standalone course as well as a specialization within our full Data Analytics Program, you&#8217;ll learn and apply the ML skills and develop the experience needed to stand out from the crowd.<\/p>\n<p><span style=\"font-weight: 400;\">For more related reading, do check out the following:<\/span><\/p>\n<ul>\n<li><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/machine-learning-engineer-salary\/\">What\u2019s the Average Machine Learning Engineer Salary?<\/a><\/li>\n<li><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/machine-learning-interview-questions\/\">22 Most-Asked Machine Learning Interview Questions (and Answers!)<\/a><\/li>\n<li><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/ai-data-analytics-tools\/\">9 of the Best AI Data Analytics Tools You\u2019ll Need<\/a><\/li>\n<\/ul>\n<h2 id=\"machine-learning-faqs\">7. Machine learning FAQ<\/h2>\n<h3>What is the difference between machine learning vs AI?<\/h3>\n<p><span style=\"font-weight: 400;\">Machine learning is a subset of AI, and it refers to the process by which computer algorithms can learn from data without being explicitly programmed. AI, on the other hand, is an umbrella term to describe software that mimics the complex functions of a human mind through computing, which includes machine learning.<\/span><\/p>\n<h3>What is the difference between machine learning vs deep learning?<\/h3>\n<p><span style=\"font-weight: 400;\">Machine learning is a broad field that includes different approaches to developing algorithms from data. Deep learning, meanwhile, is a specific type of ML technique in which machines learn through neural networks. Learn more in our <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/machine-learning-vs-deep-learning\/\" target=\"_blank\" rel=\"noopener\">guide to machine learning vs deep learning<\/a>.<\/span><\/p>\n<h3>Which is better, AI or ML?<\/h3>\n<p><span style=\"font-weight: 400;\">AI can be used for more complex applications than ML, while ML is better suited for more specific, smaller tasks. Both technologies are equally important, and your answer would depend on the context of the problem you&#8217;re trying to solve.<\/span><\/p>\n<h3>Is it hard to learn machine learning?<\/h3>\n<p><span style=\"font-weight: 400;\">It depends on the person and their level of experience. Generally, it does require quite a lot of knowledge in both computer science and mathematics to be successful in ML. However, there are also many resources available to help people learn ML more quickly.<\/span><\/p>\n<h3>Does Netflix use machine learning?<\/h3>\n<p><span style=\"font-weight: 400;\">Yes, Netflix definitely uses machine learning. According to<\/span><a href=\"https:\/\/research.netflix.com\/research-area\/machine-learning\" target=\"_blank\" rel=\"noopener\"> <span style=\"font-weight: 400;\">Netflix&#8217;s own research<\/span><\/a><span style=\"font-weight: 400;\">, they use ML to power their recommendation algorithms.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This provides you with personalized movies and show recommendations that you see in your Netflix app. This even allows for more unique recommendations where<\/span> <span style=\"font-weight: 400;\">budget-constrained algorithms can be designed<\/span><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h3>Should I learn machine learning or AI?<\/h3>\n<p><span style=\"font-weight: 400;\">You should definitely take a first look at picking up machine learning basics first, before venturing into the more advanced applications of AI, where you&#8217;ll need to learn more about deployment.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Having a basic grasp of ML will also help you build up the foundation for any AI-related projects that you might take on in the near future.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Wondering what is machine learning? Wonder no more! This beginner&#8217;s guide will show you the ropes of this exciting branch of AI behind ChatGPT and friends.<\/p>\n","protected":false},"author":159,"featured_media":27442,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_lmt_disableupdate":"yes","_lmt_disable":"","footnotes":""},"categories":[3],"tags":[],"class_list":["post-27387","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-analytics"],"acf":{"homepage_category_featured":false},"modified_by":"Matthew Deery","_links":{"self":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/27387","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/users\/159"}],"replies":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/comments?post=27387"}],"version-history":[{"count":10,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/27387\/revisions"}],"predecessor-version":[{"id":27433,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/27387\/revisions\/27433"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/media\/27442"}],"wp:attachment":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/media?parent=27387"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/categories?post=27387"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/tags?post=27387"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}