Resource recommendations for machine learning

In summary, the conversation discusses the individual's plan to change their field of study in their PhD to focus on Machine Learning, specifically in relation to strongly correlated matter. They have some prior knowledge of the subject through their MS studies and are interested in finding an introductory level book or article on Machine Learning for physicists. The suggested resources include "Hands On Machine Learning" by Aurelian Geron and online lectures by physicist Michael Nielsen.
  • #1
Luqman Saleem
18
3
I am planing to change my field (in PhD) and learn Machine Learning to differentiate different phases of strongly correlated matter. I learned Monte Carlo method in my MS and have intermediate level knowledge of topological insulators.

Before completely getting into Machine Learning, I want to go-through an introductory level book/article of Machine learning for physicists. I want to know if it is too difficult for me to learn. (is it really very difficult?)

Do you know any books/articles in which Machine Learning is explained in context of Physics?
 
Physics news on Phys.org
  • #3
@jedishrfu posted this media link on what is a neural network that I found to be the best starting point for understanding machine learning. I've studied a lot of machine learning courses and algorithms over the last year and none of the courses described it the way that that video series did. Without it, I would still be pretty confused in places.
 
  • #5
I read that and ran the code. Very good online book!
 

Related to Resource recommendations for machine learning

1. What are the best resources for learning machine learning?

There are many great resources for learning machine learning, but some popular options include online courses such as Coursera's Machine Learning course, textbooks like "Pattern Recognition and Machine Learning" by Christopher M. Bishop, and online tutorials and blogs like Towards Data Science and KDnuggets.

2. Are there any free resources for learning machine learning?

Yes, there are many free resources for learning machine learning. Some popular options include online courses on platforms like Coursera and edX, YouTube tutorials and lectures, and open-source textbooks and materials.

3. What are the best resources for staying up-to-date with machine learning advancements?

To stay up-to-date with machine learning advancements, it is helpful to follow industry leaders and experts on social media, subscribe to newsletters and blogs like Machine Learning Mastery and Data Science Central, and attend conferences and workshops.

4. How do I choose the right resource for my level of experience with machine learning?

The best resource for you will depend on your level of experience with machine learning. If you are a beginner, it is recommended to start with introductory courses and textbooks. If you have some experience, you may benefit from advanced courses and research papers. It is also helpful to read reviews and recommendations from others in the field.

5. Are there any specific resources for learning a particular machine learning technique or algorithm?

Yes, there are many resources available for learning specific machine learning techniques and algorithms. Some popular options include online courses and tutorials, textbooks, and research papers. It is also helpful to join online communities and forums where you can ask questions and learn from others who have experience with the particular technique or algorithm.

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