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Digital advertising and technology are constantly rewriting the rules. These days, it’s all about Artificial Intelligence (AI) and AI coding, machine learning, and deep learning – three buzzwords that get thrown around a lot, sometimes interchangeably.
Yet, they’re not the same thing.
Understanding the differences between machine learning and deep learning can give your digital advertising strategies the edge you need to stay ahead.
Read on to get a grasp of AI vs machine learning vs deep learning and how these latest technologies can help you significantly improve your digital marketing campaigns.
AI vs Machine Learning vs Deep Learning: What’s the Difference?
Before we discuss practical applications, let’s first get the basics straight. These terms are often used together, but they refer to different levels of sophistication in how computers learn and act on data to create ads, for example.
Artificial Intelligence (AI) is the big umbrella. It refers to the ability of a computer system to mimic human behavior and decision-making. In other words, AI is about making machines “smart” enough to solve problems without human intervention.
Machine Learning (ML) is a subset of AI that focuses on teaching machines to learn from data and make decisions without being explicitly programmed for each task. Think of machine learning as the system recognizing patterns from historical data, allowing it to predict future outcomes (for example, predicting which products a customer is likely to buy).
Deep Learning (DL) is a subset of machine learning that involves neural networks with many layers (hence “deep”). These neural networks try to mimic how the human brain processes information, making deep learning extremely powerful when it comes to handling vast amounts of data or recognizing complex patterns, like analyzing images or videos in real-time.
The difference between machine learning and deep learning comes down to complexity. Machine learning is great for more straightforward data tasks like predicting trends, while deep learning is more useful when processing unstructured data like images, voice, or videos.
Machine Learning and Deep Learning in Digital Advertising
Now, you might be wondering, “How does all this AI vs machine learning vs deep learning stuff apply to my digital advertising strategy?” Great question!
Machine Learning in Digital Advertising
Machine learning already plays a major role in the world of digital advertising. It’s the brain behind the algorithms that power targeted ads, recommendation engines, and programmatic advertising. It’s good at:
- Audience targeting
- Ad Performance prediction
- Real-time bidding (RTB)
Deep Learning in Digital Advertising
So, if machine learning is already killing it in advertising, why do we need deep learning? Because deep learning takes things to the next level by working with more complex data types and providing even deeper insights. It’s good at:
- Image and video recognition:
- Natural Language Processing (NLP)
- Sentiment analysis
- Advanced personalization
The Biggest Difference Between Machine Learning and Deep Learning in Advertising
So, what’s the difference between machine learning and deep learning in digital advertising? The simplest answer is this: machine learning handles the “what,” while deep learning digs into the “why.”
Machine learning can analyze patterns and trends, helping to create effective campaigns by predicting which strategies work best. However, deep learning goes deeper (pun intended), analyzing more complex data and revealing the underlying reasons for certain behaviors – allowing for ultra-personalized, highly targeted ads.
