course-content
best-of-ml-python
course-content | best-of-ml-python | |
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14 | 16 | |
2,591 | 15,364 | |
0.9% | 0.9% | |
7.9 | 7.8 | |
2 months ago | 1 day ago | |
Jupyter Notebook | Python | |
Creative Commons Attribution 4.0 | Creative Commons Attribution Share Alike 4.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
course-content
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Can a CS student get a phd In Neuroscience?
Yes. And if you want to get a jump start on what a computational neuroscience PhD might look like, check out our materials at https://compneuro.neuromatch.io. Like a PhD in a box... and all free to use/explore!
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Ask HN: How to get back into AI?
The neuromatch computational neuroscience course also seems quite interesting, though maybe less of practical use.
https://compneuro.neuromatch.io/
Recent research like "Relating transformers to models and neural representations of the hippocampal formation" might make it more relevant though (https://arxiv.org/abs/2112.04035v2)
quote from the abstract of that paper:
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Looking for neuro-related research ideas for a masters in mathematics
check out the curated datasets and project outlines for Neuromatch Academy's computational neuroscience course for some inspiration! https://compneuro.neuromatch.io
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How can I become a strong candidate for a comp. neuroscience MS/Ph.D. program?
One possible thing I saw is taking https://compneuro.neuromatch.io/ courses, Although I'm not sure of the effect it adds to my CV.
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AskScience AMA Series: We are seven leading scientists specializing in the intersection of machine learning and neuroscience, and we're working to democratize science education online. Ask Us Anything about computational neuroscience or science education!
https://github.com/NeuromatchAcademy/course-content https://github.com/NeuromatchAcademy/course-content-dl
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We are Konrad Kording, Megan Peters, Brad Wyble, Dan Goodman, Gunnar Blohm, and Sean Escola, and we're a group of scientists who started a major, international online summer school aiming to democratize science education and make it accessible to all. Ask Us Anything!
If you'd like to learn more about it, you can check out last year's Comp Neuro course contents here, last year's Deep Learning course contents here, read the paper we wrote about the original NMA here, read our Nature editorial, or the Lancet article00074-0/fulltext) about us.
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Help with computational modelling
Check out Neuromatch Academy. If you don't have time or inclination to do the summer school this summer, you can simply access all the videos and tutorials for free at https://compneuro.neuromatch.io
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Best sources for someone interested in pursuing computational neuroscience?
https://compneuro.neuromatch.io has all the materials for free, including lecture videos and hands on Google Colab notebook programming exercises. You can also apply to take the course synchronously with a "pod" of 10 other people in a 3-week summer intensive online, with a TA to guide you and group projects to cement your understanding. To apply, check out http://academy.neuromatch.io. Applications open soon and it sounds like you'd be a great fit.
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Some questions on studying computational neuroscience
Yes, Neuromatch Academy. Their whole course is available as a Jupyter Book here
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What psychology papers to read as a computer science researcher looking to break into cognitive science research?
Maybe better than any single book or paper, I would recommend you check out neuromatch academy. There are 2 courses, computational neuroscience and deep learning and everything is free and open source. Play with the code, listen to the lectures, even do a "canned project" if you want experience.
best-of-ml-python
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Ask HN: How to get back into AI?
For Python, here's a nice compilation: https://github.com/ml-tooling/best-of-ml-python/blob/main/RE...
- Best-Of Machine Learning with Python
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Questions regarding Job Requirements for data analyst to data science transition?
You will need numpy, scipy, pandas, scikit-learn, Keras/tensorflow/pytorch, xgboost and many many many others. See this list for example.
- Awesome list of ML
- Are there any speech recognition modules so I can write one and do not have to rely on google and the likes?
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Learning opencv
Take a look at this list on github. It has a pretty comprehensive list of python image libraries.
- Best-of Machine Learning with Python
- 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
What are some alternatives?
stats305c - STATS305C: Applied Statistics III (Spring, 2023)
Awesome-WAF - 🔥 Web-application firewalls (WAFs) from security standpoint.
Kilosort - Fast spike sorting with drift correction for up to a thousand channels
ktrain - ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
dtale - Visualizer for pandas data structures
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
ffcv - FFCV: Fast Forward Computer Vision (and other ML workloads!)
Neuro-Breakout - Play breakout using the Myo Armband by Thalmic labs using python.
awesome-python - An opinionated list of awesome Python frameworks, libraries, software and resources.
course-content-dl - NMA deep learning course
kmodes - Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data