Introduction To Machine Learning For Data Science In 2021 [Free Online Course] - TechCracked

Overview Of What Is Machine Learning & Why You Should Learn It. Complete Intro To Data Science With Python Course

What you'll learn

• The Impacts Machine Learning and Data Science is having on society.
• To know what problems Machine Learning can solve, and how the Machine Learning Process works.
• To really understand computer technology has changed the world, with an appreciation of scale.
• How to avoid problems with Machine Learning, to successfully implement it without losing your mind!

Description

What Is Machine Learning?

A subset of artificial intelligence (AI), machine learning (ML) is the area of computational science that focuses on analyzing and interpreting patterns and structures in data to enable learning, reasoning, and decision-making outside of human interaction. Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyze and make data-driven recommendations and decisions based on only the input data. If any corrections are identified, the algorithm can incorporate that information to improve its future decision-making.

How Does Machine Learning Work?

Machine learning is made up of three parts:

• The computational algorithm is at the core of making determinations.
• Variables and features that make up the decision.
• Base knowledge for which the answer is known that enables (trains) the system to learn.

Initially, the model is fed parameter data for which the answer is known. The algorithm is then run, and adjustments are made until the algorithm’s output (learning) agrees with the known answer. At this point, increasing amounts of data are input to help the system learn and process higher computational decisions.

Why Is Machine Learning Important?

Data is the lifeblood of all businesses. Data-driven decisions increasingly make the difference between keeping up with the competition or falling further behind. Machine learning can be the key to unlocking the value of corporate and customer data and enacting decisions that keep a company ahead of the competition.

Machine Learning Use Cases

Machine learning has applications in industries, including manufacturing, retail, healthcare and life sciences, travel and hospitality, financial services, energy, feedstock, and utilities. Use cases include:

• Manufacturing. Predictive maintenance and condition monitoring
• Retail. Upselling and cross-channel marketing
• Healthcare and life sciences. Disease identification and risk satisfaction
• Travel and hospitality. Dynamic pricing
• Financial services. Risk analytics and regulation
• Energy. Energy demand and supply optimization

Also See : Live Coding with Data Structures for campus/internship/jobs

Enroll Now