Machine Learning Algorithms | Machine Learning Tutorial | Data Science Algorithms | Simplilearn

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This Machine Learning Algorithms Tutorial video will help you learn you what is Machine Learning, various Machine Learning problems and the algorithms, key Machine Learning algorithms with simple examples and use cases implemented in Python. The key Machine Learning algorithms discussed in detail are Linear Regression, Logistic Regression, Decision Tree, Random Forest and KNN algorithm. This Machine Learning Algorithms tutorial is designed for beginners to understand which algorithm to use when, how each algorithm works and implement it on Python with real-life use cases.

Below topics are covered in this Machine Learning Algorithms Tutorial:

1. Real world applications of Machine Learning
2. What is Machine Learning?
3. Processes involved in Machine Learning
4. Type of Machine Learning Algorithms
5. Popular Algorithms with hands-on demo
– Linear regression
– Logistic regression
– Decision tree and Random forest
– N Nearest neighbor

What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

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About Simplilearn Machine Learning course:

A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.

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Why learn Machine Learning?

Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.

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What skills will you learn from this Machine Learning course?

By the end of this Machine Learning course, you will be able to:

1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.

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Who should take this Machine Learning Training Course?

We recommend this Machine Learning training course for the following professionals in particular:

1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning

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