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Data Science VS Machine Learning: Which One To Pick For 2022!
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Data Science and Machine Learning are both lucrative fields within artificial intelligence and tech. But which one is the best to learn? In this video I talk about exactly what is data science and machine learning and what is the difference between them.
What is Data Science:
Data Science is the process of making sense of data, often times larges amounts of data (also known as big data), and identifying meaningful patterns which are useful for making business decisions and can play a significant role in creating solutions to problems. It's used in a multitude of industries; finance and banking, transportation, health, etc.
What is Machine Learning:
Machine learning on the other hand, refers to the algorithms which machine learning engineers and even data scientists use in order to make a machine learn from data and apply the learning to new sets of data and get the answers we are looking for.
Where do they overlap:
Data science is not machine learning, but they do overlap, lots of data scientists make use of machine learning and vice versa. However, there are parts of machine learning that are completely unrelated to data science. A data scientist's job includes translating business questions into specific quantitative questions that can be answered with available data using statistical methodologies. In cases where questions cannot be answered with available data, they work with engineers to produce the required data.
Machine learning engineers design, implement and deliver ML components along with high quality software to solve complex problems. They also develop ML models using variety of ML design approaches as well as making use of knowledge such as data processing, regression, clustering, recommendations, classification, experimentation, model optimization.
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What is Data Science:
Data Science is the process of making sense of data, often times larges amounts of data (also known as big data), and identifying meaningful patterns which are useful for making business decisions and can play a significant role in creating solutions to problems. It's used in a multitude of industries; finance and banking, transportation, health, etc.
What is Machine Learning:
Machine learning on the other hand, refers to the algorithms which machine learning engineers and even data scientists use in order to make a machine learn from data and apply the learning to new sets of data and get the answers we are looking for.
Where do they overlap:
Data science is not machine learning, but they do overlap, lots of data scientists make use of machine learning and vice versa. However, there are parts of machine learning that are completely unrelated to data science. A data scientist's job includes translating business questions into specific quantitative questions that can be answered with available data using statistical methodologies. In cases where questions cannot be answered with available data, they work with engineers to produce the required data.
Machine learning engineers design, implement and deliver ML components along with high quality software to solve complex problems. They also develop ML models using variety of ML design approaches as well as making use of knowledge such as data processing, regression, clustering, recommendations, classification, experimentation, model optimization.
-------------------------------------------------------------------------
LINKS:
--------------------------------------------------------------------------
--------------------------------------------------------------------------
MORE VIDEOS:
--------------------------------------------------------------------------
📌I'm Starting My Machine Learning Company (Day 1)
📌Top Machine Learning Certifications For 2021
📌Why You Should NOT Learn Machine Learning!
📌How I Learnt Machine Learning In 6 Steps (3 months)
📌How To Learn Machine Learning For Free
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