Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) Data Science
Even the most complex topics can be segregated in easy to consume buckets. Let me try to explain them
Artificial Intelligence (AI) Human Intelligence Exhibited by Machines
Intelligence exhibited by machines
Broadly defined to include any simulation of human intelligence
Expanding and branching areas of research, development, and investment
Includes robotics, rule-based reasoning, natural language processing (NLP), knowledge representation techniques (knowledge graphs) …
Machine Learning (ML) An Approach to Achieve Artificial Intelligence
Subfield of AI that aims to teach computers the ability to do tasks with data, without explicit programming
Uses numerical and statistical approaches, including artificial neural networks to encode learning in models
Models built using “training” computation runs or through usage
Deep Learning (DL) A Technique for Implementing Machine Learning
Subfield of ML that uses specialized techniques involving multi-layer (2+) artificial neural networks
Layering allows cascaded learning and abstraction levels (e.g. line -> shape -> object -> scene)
Computationally intensive enabled by clouds, GPUs, and specialized HW such as FPGAs, TPUs, etc.
Data Science – Scientific methods, algorithms and systems to extract knowledge or insights from big data
Also known as Predictive or Advanced Analytics
Algorithmic and computational techniques and tools for handing large data sets
Increasingly focused on preparing and modeling data for ML & DL tasks
Encompasses statistical methods, data manipulation and streaming technologies (e.g. Spark, Hadoop)
Key skill and tools behind building modern AI technologies
Your smartphone, your house, your car, and your bank all use artificial intelligence on a daily basis. Sometimes it’s easy to understand, when you ask Siri, Cortana or OK Google to get you directions. Sometimes it’s less obvious, like when you make an abnormal purchase on your credit card and don’t get a fraud alert from your bank. AI, ML and DL are everywhere and Data Science is the interdisciplinary field of methonds to extract the knowledge needed. All these technologies are making a huge difference in our lives every day and evoloving fast by a magnitude of people working to improve them consistently.
