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This Machine Learning basics video will help you understand what is Machine Learning, what are the types of Machine Learning, what is Supervised & Unsupervised Machine Learning, what is Reinforcement Learning and will also explain how Machine Learning is being used in various businesses. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, put simply, the iterative aspect of machine learning is the ability to adapt to new data independently. This is possible as programs learn from previous computations and use “pattern recognition” to produce reliable results. Machine learning is starting to reshape how we live, and it’s time we understood what it is and why it matters. Now, let us deep dive into this short video on Machine learning and understand the basics of Machine Learning.
Below topics are explained in this Machine Learning basics video:
1. What is Machine Learning? (00:52)
2. What is Supervised Learning? (01:25)
3. What is Unsupervised Learning? (01:52)
4. What is Reinforcement Learning? (02:25)
5. Simplilearn’s Machine Learning certification course (03:54)
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Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy
#MachineLearning #MachineLearningAlgorithms #WhatisMachineLearning #MachineLearningBasics #SimplilearnMachineLearning #MachineLearningCourse
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.
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.
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.
4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems
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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Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you. Thanks for watching the video. Cheers!
Can you show examples in excel with fields of supervised learning, unsupervised learning, reinforcement learning
Still I need better examples to understand reinforcement learning
Well explained Machine Learning concept in 5 minutes. Thumbs up.
Good job Simplilearn team! Please correct the sentence at 1:42. It should be "Classification and Regression are the types of SUPERVISED learning".
fraud detection might me considered as an unsupervised learning. Rest options would label their examples to be executed.
Understandable info
Is the order of machine learning tutorials videos perfect?
I love this …Thank you for providing useful concepts with real time examples like this 👌
@time 1:42 it showed as unsupervised learning instead of supervised.
Love the way you put things. Nice work guys. Subscribed 🙂
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