{"id":60728,"date":"2019-03-19T00:37:58","date_gmt":"2019-03-19T00:37:58","guid":{"rendered":"https:\/\/explore.local\/2019\/03\/19\/degreed-does-data-machine-learning\/"},"modified":"2025-04-04T19:17:05","modified_gmt":"2025-04-04T19:17:05","slug":"degreed-does-data-machine-learning","status":"publish","type":"post","link":"https:\/\/degreed.com\/experience\/fr\/blog\/degreed-does-data-machine-learning\/","title":{"rendered":"Degreed Does Data: Machine Learning"},"content":{"rendered":"\n

Data, machine learning, and artificial intelligence are disrupting everything we know, in ways that most of us don\u2019t understand \u2014 yet. To help you keep up, we\u2019ve launched a new series, Degreed Does Data<\/em>. We\u2019ll dive deep into these topics, simplify their complexities, explain their potential impact, and break down the dramatic ways they\u2019ll change the industry.<\/p>\n\n\n\n

Today, we\u2019re handling a hot one: machine learning. Information \u2014 on just about everything \u2014 has never been more available. It\u2019s what makes machine learning so valuable and necessary. So what is it? Why do companies need to start paying attention to it? And how can these same companies leverage its capabilities? <\/p>\n\n\n\n

What is Machine Learning?<\/h2>\n\n\n\n
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Definition: <\/em><\/strong>training a software program with examples, experiments, or experiences, so that it can recognize patterns, make predictions, and complete tasks.<\/em><\/p>\n\n\n\n

Now that computers can handle and process such huge amounts of information, machine learning allows us to connect the dots in ways that we never could. We can drive down thousands of streets with computer vision, while our cars see the entire road at all times. By the same token, our phones can understand anything from Albanian to Zulu after analyzing billions of soundbites using natural language processing.<\/p>\n\n\n\n

What\u2019s most exciting is that machine learning is still in its infancy \u2014 despite being this century\u2019s most important breakthrough in artificial intelligence. Its capabilities and the doors it can open will only continue to grow \u2014 and not in the robots-are-taking-over kind of way.<\/p>\n\n\n\n

Machine Learning Applied<\/h2>\n\n\n\n
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This begs the question, how do companies adapt to keep up with machine learning? Maybe they hire software engineers to replace their truck drivers with autonomous vehicles. Or re-train their international sales team with language learning apps tailored to each person\u2019s strengths and weaknesses. Additionally, companies can leverage machine learning algorithms to boost efficiency and streamline processes<\/a> for everything from research and development to sales to marketing. <\/p>\n\n\n\n

Of course, the smartest approach is comprehensive, especially in the L&D world. By applying all the necessary elements of machine learning, company learning can vastly improve, leading to more informed, data-driven decisions. In a nutshell, L&D needs software that helps the right people learn the right things at the right time.<\/p>\n\n\n\n

Machine learning can also predict what skills will be in demand. From there, it can suggest what workers should learn and identify which resources are most effective. One of machine learning\u2019s greatest attributes is automatically offering relevant mini-lessons to help employees with any tasks or goals they\u2019re working on, ensuring they\u2019re continuously ahead of the curve. We see this with IBM Watson Career Coach<\/a>, which fosters employee engagement and guides careers. By using Career Coach, IBM employees can get their skill-sets analyzed, as well as receiving career recommendations and relevant upskilling<\/a> suggestions.<\/p>\n\n\n\n

Asking your SaaS Vendors about Machine Learning<\/h2>\n\n\n\n
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What exactly can this system do with machine learning?<\/em><\/strong><\/p>\n\n\n\n

Some vendors are trying to hide behind the hype<\/a> of machine learning. Their software is not evolving and only lists \u201crecommended\u201d content. That\u2019s fine if you\u2019re mindlessly binging TV shows \u2014 we\u2019re finally all caught up on Game of Thrones \u2014 but it\u2019s not enough in the learning context. True machine learning gives you a platform that understands its unique users, strengthens its own weaknesses, and adapts to trends that it discovers. There\u2019s no need to settle for recommendations.<\/p>\n\n\n\n

How has machine learning already changed your work?<\/em><\/strong><\/p>\n\n\n\n

Yes, machine learning is the future, but it\u2019s also the present. The most agile competitors are already applying these technologies in every industry. Even DIY tinkerers have figured out new uses for machine learning. What your organization needs are tools that keep everyone ahead of the latest learning trends. This ensures your vendor understands how your industry is changing and can explain how they\u2019ll help you adapt.<\/p>\n\n\n\n

Which types of machine learning does your software use?<\/em><\/strong><\/p>\n\n\n\n

You should know two main approaches: supervised learning means the program trains with data that humans already sorted out, following directions until it sees the pattern for itself. Unsupervised learning takes off the training wheels, so the system runs through unclassified data while finding connections and creating its own categories. <\/p>\n\n\n\n

How much data is required for machine learning to be useful?<\/em><\/strong><\/p>\n\n\n\n

People usually underestimate how much data they need. In the case of machine learning, more is always better. Even 100,000 records are hardly enough. The machine can only predict based on the data it has. To catch fraud, banks must track data on each transaction \u2014 location, currency, credit history, and more. <\/p>\n\n\n\n

Similarly, learning systems can only predict relevant content if they\u2019re tracking the right user data \u2014 interests, social network accounts, or learning history. Once you have millions of these examples to train your system, it becomes clear what success looks like and your algorithm will reach its potential.<\/p>\n\n\n\n

More Machine Learning Resources<\/h2>\n\n\n\n
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Understanding Machine Learning<\/em><\/strong><\/a> (infographic)<\/em><\/strong><\/p>\n\n\n\n

Futurism.com offers a straightforward overview of this infographic, which includes the history, approaches, and applications of machine learning.<\/p>\n\n\n\n

What is Machine Learning?<\/em><\/strong><\/a> (5 min video)<\/em><\/strong><\/p>\n\n\n\n

This video is the first in a series from Google, and it begins by explaining how machine learning makes data meaningful.<\/p>\n\n\n\n

How Machine Learning is Changing the World \u2014 And Your Everyday Life<\/em><\/strong><\/a> (6 min article)<\/em><\/strong><\/p>\n\n\n\n

Entrepreneur Magazine details how machine learning already works in education, law, transportation, healthcare, and our homes.<\/p>\n\n\n\n

Machine Learning and Artificial Intelligence<\/em><\/strong><\/a> (12 min video)<\/em><\/strong><\/p>\n\n\n\n

This thorough explanation from Crash Course is part of a series that includes helpful videos on computer vision and natural language processing.<\/p>\n","protected":false},"excerpt":{"rendered":"

Data, machine learning, and artificial intelligence are disrupting everything we know, in ways that most of us don\u2019t understand \u2014 yet. To help you keep up, we\u2019ve launched a new series, Degreed Does Data. We\u2019ll dive deep into these topics, simplify their complexities, explain their potential impact, and break down the dramatic ways they\u2019ll change […]<\/p>\n","protected":false},"author":110,"featured_media":60734,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[570,572],"tags":[539,546],"post_folder":[],"class_list":["post-60728","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-about-degreed","category-ai-innovation-in-learning","tag-degreed-products","tag-learning-technology"],"acf":[],"yoast_head":"\nIntroduction to Machine Learning for L&D | Degreed<\/title>\n<meta name=\"description\" content=\"Information \u2014 on just about everything \u2014 has never been more available. It\u2019s what makes machine learning so valuable and necessary. 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