Artificial Intelligence is an umbrella term that covers a variety of new-age cognitive technologies like machine learning, deep learning, NLP, and neural networks. AI enables us to build intelligent systems capable of performing business processes that previously required human interaction and intelligence.
Artificial intelligence enables machines or programs to carry out tasks in a “smart” way. By integrating AI, a program or machine reacts with human-like behaviors to real-world scenarios via its application of contemplation, judgment, and intention.
In machine learning, a machine or computer system learns how to make accurate predictions—or make “smart” decisions after receiving a particular set of data. It is an AI-based concept that allows machines to identify patterns, learn from previous experiences, and make adequate decisions without or little human intervention.
Both machine learning and deep learning systems are capable of both supervised or unsupervised learning. They use historic data and produce predictive models that can automate business processes, which requires human intelligence. A typical AI/data science project life cycle starts from data extraction, exploratory data analysis (EDA) and covers various advanced stages like feature engineering, model selection, hyperparameter tuning, etc. Not to mention, there’s a huge demand for artificial intelligence jobs in the industry.
