Artificial Intelligence vs Machine Learning vs Deep Learning
MuthuKumaran Singaravelu
CTO | AI & Web Development Expert | Keynote Speaker | Guest Lecturer | Digital Transformation Strategist
Today's IT world can be confusing, especially when many fields of computer science intersect with one another. We wanted to help break it down. Here I explain In AI, ML and DL what they're used for and some examples of algorithms used in each.
1. Artificial Intelligence
AI is field of computer Science technology that how we create intelligent machines that exhibit intelligence understands their environment take actions/make decision to maximize the probability of success at a goal
Where it is used for:
Artificial intelligence employed in numerous fields likes speech recognition, learning, planning, and problem solving.
It is used for solve issues for problems or build automated machine-controlled decisions for tasks that controlled by machines exploits intelligence like human.
Limits of Artificial Intelligence
"Strong" Artificial Intelligence
"Weak" Pattern-Based Artificial Intelligence
Two Major AI Techniques
Logic and Rules-based Approach
Machine Learning (Pattern-Based Approach)
Some AI Algorithms
Q- Learning
Actor-Critic Methods
Reinforce
Deep Deterministic Policy Gradient (DDPG)
Multi-Agent Deep Deterministic Policy Gradient (MADDPG)
2. Machine Learning:
Machine Learning is a sub field of an Artificial Intelligence (AI) discipline that geared towards the technological development of human knowledge.
Algorithms notice patterns in knowledge and infer rules on their own. Patterns “Learn” from knowledge and improve over time. These patterns are used for automation or prediction.
Where it is used for
Machine Learning is that the development of computing through develop and capture new patterns and trend detection for decisions.
Some ML Algorithms
Linear Regression
Logistic Regression
K-means Clustering
Decision Trees
Sentiment Analysis
Support Vector Machine
3. Deep Learning:
Deep Learning is a collection of algorithms employed in machine learning, used to model high-level abstractions in knowledge with model architectures, which are composed of multiple non-linear transformations. Deep learning is that the fastest-growing field in artificial intelligence (AI).
Where it is used for:
Deep Learning is a specific approach used for training and building neural networks, which are used for decision-making.
It is used in various Intelligent Apps, Analytics tools and Intelligent Things.
Algorithms:
Siamese Networks
Transfer Learning
Recurrent Neural Networks (RNN’s)
Convolutional Neural Networks (CNN’s)
Transformer
Please leave a comment and let me know if you have any suggestions or queries.
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