Mathematics for Machine Learning [Full Course] | Essential Math for Machine Learning | Edureka

This Edureka video on 'Mathematics for Machine Learning' teaches you all the math needed to get started with mastering Machine Learning. It teaches you all the necessary topics and concepts of Linear Algebra, Multivariate Calculus, Statistics, and Probability and also dives into the actual implementation of these topics.

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#Edureka #MachineLearning #MathematicsForMachineLearning #
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How does it work?

1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training, you will be working on a real-time project for which we will provide you with a Grade and a Verifiable Certificate!

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About the Course

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in Python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in Python programming language to enhance your learning experience.
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After completing this Machine Learning Certification Training using Python, you should be able to:

Gain insight into the 'Roles' played by a Machine Learning Engineer
Automate data analysis using python
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Explain Time Series and it’s related concepts
Gain expertise to handle business in the future, living the present
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Why learn Machine Learning with Python?

Data Science is a set of techniques that enables computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.

[meghajha]

Edureka team is appreciable really. They are doing a lot for students like us who are interested in such things but couldn't afford to pay for such courses. Thank you so much for introducing about new age technologies to all of us. Great work. Keep it up. God bless you all

[soumya]

This was the tutorial I was looking for months and years!!

[MovieManiacs_]

In the scalar multiplication part grow and shrink of the vector will depend on whether k >1 or k<1 not the positive or negative value of k

[saurav]

Good Tutorial. However, it is to be noted that for matrix multiplication, the columns of first matrix should be equal to the rows of second matrix. It's mentioned the other way around at 16:29 (the rows of first matrix should be equal to columns of second matrix)

[adamdost]

Edureka channel has got the qualities of a Mother. Always Kind and helping

[iloveiit]

Just looking for this video from a long time and now I got it

[neerajlamsal]

Thank you so much for this video edureka I was just going to join a collage for learning maths for ML

[kylehostetter]

This is an amazing video. I have been wanting to actually have a full understanding of what is going on in the background. I think that this was straight to the point, and I LOVE it! Now I do believe if you don't understand the material here, I would suggest looking some things up! But I think that this is a GREAT video that give a simple, yet concise representation of the math needed.

[schzo]

Thanks a lot once again! Your courses always helps me getting better and better at programming

[NishantSingh-pxjm]

Best channel I found on internet ✌
Thanks for these high quality content.

[spurthygopal]

I am learning lot from this channel! Thanks a lot for this video. Keep updating more such videos

[riviera]

What a wonderful way of transmitting knowledge! Beyond adjectives...

[jippyjlock]

Thank you so much for making this. It was basically exactly what I was looking for.

[bagoesheikhal]

Man, this is very helpfull. thank you sir

[thebrokeartist]

Thank you so much Edureka for helping us students 😊😊

[yashashreejoshi]

THANK YOU SO MUCH EDUREKA ..God bless you ❤

[Joy-jppm]

Sir, I have a doubt at 14:48 seconds, How we get (4 2 4 1)+ (2 3 1 4)

[ericgacoki]

Thanks so much. You always bring us what we want

[HackingWithCoffee]

Awesome video, waiting for it long long time ago, finally....

[chandrasekharanumula]

Excellent content . Thank you very much edureka!