Overview¶
AI : Artificial Intelligence¶
At its core : AI is the science and engineering of creating intelligent machines(or)systems that can perform tasks that typically require human intelligence.
The basic analogy of this field is to mimic a human brain, that simulates human intelligence into a machine and programs it to think and behave like humans. This field involved developing algorithms, which analyzes data and perform human-like action. For example, understanding natural language like a human, and recognizing images to understand the things inside the image.
If I asked you from this image, how many objects are in above picture and what are that objects ?
So you can easily identify with your eyes. because you know these objects before.
But by asking the same question to the machine, you need to feed some intelligence into the machine so that it can identify these objects. in order to make a machine talk like a human and the process which involves making a machine talk comes under the artificial intelligent domain.
What “Intelligence” Means in AI:¶
Learning from experience
Understanding complex concepts
Reasoning and problem-solving
Perceiving the environment
Using language
Making decisions
ML : Machine Learning¶
we can say Machine Learning is a subfield of AI. Where ML algorithms can learn from data to improve the accuracy and performance of AI systems.
“the field of study that gives computers the ability to learn without explicitly being programmed.” — Arthur Samuel
The difference between AI and ML is frequently misunderstood. People had a mindset that Machine learning learns and predicts based on passive learning or you can say learning from past history of data. And AI (Artificial intelligence) uses an agent to interact with the environment to learn and take action to maximize its chance of success. We know this technique as Reinforcement learning.
we can just conclude :
ML uses multiple method’s called algorithm(s) to make AI systems more powerful.
DL : Deep Learning¶
Deep Learning focuses on learning the hidden patterns of the data and making intelligent decisions without any explicit programming. Deep Learning is a subfield of Machine learning through which you can train an AI system.
To understand Deep Learning, you have to understand Artificial Neural Networks.
What is neuron ?¶
Think of a artificial neuron as a small processing unit that receives data, adjusts its importance, and outputs a value that helps the system to learn the patterns, and passes information to other neurons.
What is neural network ?¶
An Artificial Neural Network is a machine learning model that stacks simple “neurons” in layers and learns pattern from data to map inputs to outputs.
DS : Data Science¶
Data Science is an interdisciplinary field that involves collecting, processing, analyzing, and interpreting data to solve real-world problems and inform decision-making.
Data science combines various fields. for example Statistics, Computer Science, Domain Specific Knowledge, Visualization, data engineering techniques, data quality techniques, and data profiling techniques to analyze and interpret complex data sets.
Data science combines various fields, for example:¶
Statistics & Mathematics for analysis and modeling
Computer Science & Programming for data processing and algorithm implementation
Domain Knowledge (business, healthcare, etc.) for context and relevance
Data Visualization & Communication for presenting insights effectively
Conclusion¶
AI : A system or model that can do/have Human Like Intelligence.
ML : Set of alogithms to make system learn without rules.
DL : uses Neurol Networks to learn from data.
DS : involves statistics, programming, ML to turn raw data into actionable insights.