How to become a Machine Learning Engineer?

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How to become a Machine Learning Engineer, If you’re wondering, “How do I learn Machine Learning?” then you’ve come to the perfect spot.

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Machine learning is in high demand these days, and it has a wide range of applications. Many software professionals are switching to machine learning because it is quite popular and pays well.

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How to become a Machine Learning Engineer?

So, how can I study machine learning, is the next thing that comes to mind, and what are the steps to learning machine learning?

Basic Calculus is essential to study machine learning. Machine Learning is based on optimization, which necessitates Calculus expertise.

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As a result, you should have a rudimentary understanding of limits, functions, maxima, minima, and other concepts.

Calculus can be learned using engineering maths books or online. If you want to learn Calculus, you should use this book.

Linear Algebra is the next prerequisite for ML because you will be dealing with vectors and matrices in ML. You should be familiar with linear algebra ideas.

The key subjects in ML are eigenvalues and eigenvectors. This book, Linear Algebra, and Optimization for Machine Learning can help you learn Linear Algebra for Machine Learning.

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Statistics/ Probability– You should also have a rudimentary understanding of probability.

Book, Data Science and Machine Learning: Mathematical and Statistical Methods, might help you with your statistics understanding.

You don’t need to be an expert in any of these areas, but you should be familiar with terminology like subspace, independent, and basis.

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What is the best way to learn Machine Learning?

After you’ve finished with arithmetic, you’ll need to move on to ML. To do so, you’ll need to complete the following steps:

First, learn whatever programming language you can get your hands on. You can learn any language for machine learning, but we would like Python because it is straightforward to learn and utilize.

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Learn the fundamentals of machine learning methods such as classification, clustering, regression, and others. You can learn ML by taking any decent online course or reading books.

As a novice, you should begin with the fundamentals and work your way up to more difficult materials.

If you’re a beginner, Tom Mitchell’s book on Machine Learning is the greatest place to start.

Start practicing with Kaggle once you’ve gathered all of the fundamentals. Kaggle is a prominent machine learning competition platform where you can experiment with real-world data and gain a sense of how machine learning is applied in the real world.

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If you’re seeking Machine Learning Courses, this is a list of the Best Machine Learning Courses available online.

  1. Machine Learning (Coursera)
  2. Deep Learning Specialization (
  3. Machine Learning A-Z™: Hands-On Python & R In Data Science -Udemy
  4. Deep Learning (Udacity)
  5. Machine Learning with Python (Coursera)
  6. Machine Learning Engineer Masters Program (Edureka)
  7. AI & Deep Learning with TensorFlow (Edureka)
  8. Intro to Machine Learning with TensorFlow (Udacity)
  9. Become a Machine Learning Engineer (Udacity)
  10. Advanced Machine Learning Specialization
  11. Get started with Machine Learning (Codecademy)
  12. Learn the Basics of Machine Learning (Codecademy)
  13. Mathematics for Machine Learning Specialization (Coursera)
  14. Python for Data Science and Machine Learning Bootcamp- Udemy

We will add up more courses on this post, so bookmark the page. Happy Learning!

To read more visit How to become a Machine Learning Engineer?.

If you are interested to learn more about data science, you can find more articles here finnstats.

The post How to become a Machine Learning Engineer? appeared first on finnstats.

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