Machine Learning (ml) Vs. Artificial Intelligence (ai) — Crucial Differences

By Author: Charter Global Inc.
Total Articles: 71
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Artificial intelligence and Machine Learning are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems.

Although these are two related technologies and sometimes people use them as a synonym for each other, but still both are two different terms in various cases.

On a broad level, we can differentiate both AI and ML as:

https://www.charterglobal.com/machine-learning-vs-artificial-intelligence-whats-the-difference/

Artificial Intelligence vs. Machine Learning: Required Skills

Because artificial intelligence is a catchall term for smart technologies, the necessary skill set is more theoretical than technical. Machine learning professionals, on the other hand, must have a high level of technical expertise.

Artificial Intelligence Skills

People pursuing a career in artificial intelligence must have a foundation in:

1. Algorithms, and techniques for analyzing them
2. Machine learning and how to apply techniques to draw inferences from data
3. The ...
... ethical concerns in developing responsible AI technologies
4. Data science
5. Robotics
6. Java programming
7. Programming design
8. Data mining
9. Problem-solving

Machine Learning Skills

People pursuing a career in machine learning must have a foundation in:

1. Applied mathematics
2. Neural network architectures
3. Physics
4. Data modeling and evaluation
5. Natural language processing
6. Programming languages
7. Probability and statistics
8. Algorithms

The Future is now with AI and ML

So, by now, you’ve learned the basic differentiating factors between ML and AI. Machine learning uses past experiences to look for learned patterns, while Artificial Intelligence uses the experiences to acquire knowledge and skills, then applies that knowledge to new scenarios.

It’s clear that both AI and machine learning have valuable business applications, empowering companies to respond quickly and accurately to changes in customer behavior and solve critical business problems.

As the adoption of AI and ML become more commonplace, namely predictive analytics and data science will see a massive uptake in virtually all industries across the marketplace.