best-of-ml-python
NNfSiX
| best-of-ml-python | NNfSiX | |
|---|---|---|
| 16 | 46 | |
| 15,364 | 1,354 | |
| 0.7% | - | |
| 7.8 | 0.0 | |
| 1 day ago | 7 months ago | |
| Python | C++ | |
| Creative Commons Attribution Share Alike 4.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
best-of-ml-python
-
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
-
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?
-
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.
NNfSiX
-
Are there any books I should read to learn machine learning from scratch?
I've been rather enjoying "Neural Networks from Scratch" (https://nnfs.io/)
-
Ask HN: Those learning about neural networks, what do you find most difficult?
I haven't gotten super deep into it yet, but https://nnfs.io/ has been good in my opinion. The book slowly replaces written and explained code with numpy equivalents to keep the examples fast. Plus the accompanying animations are also useful. I would be curious what others think on it too.
- Gutes Einführungsbuch zu KI
- [Deep Learning] Neural Networks from Scratch in Python
- What do I get a programming obsessed high school boy for his birthday? I actually need advice
-
GPT in 60 Lines of NumPy
For those curious to writing "gradient descent with respect to some loss function" starting from an empty .py file (and a numpy import, sure), can't recommend enough Harrison "sentdex" Kinsley's videos/book Neural Networks from Scratch in Python [1].
[1] https://youtu.be/Wo5dMEP_BbI?list=PLQVvvaa0QuDcjD5BAw2DxE6OF... https://nnfs.io
-
Ask HN: What are the foundational texts for learning about AI/ML/NN?
Not sure if foundational (quite a tall order in such a fast-moving field), but for sure a nice introduction into neural networks, and even mathematics in general (because it's nice to see numbers in action beyond school-level algebra):
Harrison Kinsley, Daniel Kukiela, Neural Networks from Scratch, https://nnfs.io, https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0Qu...
-
Ask HN: How to get back into AI?
Have you had a look at https://nnfs.io/ ? I bought the book and am gearing up to start working through it, I would be interested to know your thoughts. Generally I want to chart a personal curriculum from data engineer to practical application of modern AI to real business problems.
-
Programming an AI as a beginner
You can check out Neural Networks from Scratch in Python for an introduction to neural networks, which can be used for image classification. Please be forewarned that you'll need the mathematics necessary to read through this book - however, I'm assuming that since you've selected writing such an algorithm(s) in Python for your final school project that you're aware of such.
-
Moved to amd today and holy it's amazing
I am planning on working my way through Neural Networks From Scratch (https://nnfs.io/) in a few months just to build my understanding. After that I'm hoping to be able to figure out the best path for a couple of projects I have in mind.
What are some alternatives?
Awesome-WAF - 🔥 Web-application firewalls (WAFs) from security standpoint.
deeplearning-notes - Notes for Deep Learning Specialization Courses led by Andrew Ng.
ktrain - ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
ML-From-Scratch - Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
dtale - Visualizer for pandas data structures
micrograd - A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
ffcv - FFCV: Fast Forward Computer Vision (and other ML workloads!)
deepnet - Educational deep learning library in plain Numpy.
awesome-python - An opinionated list of awesome Python frameworks, libraries, software and resources.
minGPT - A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
kmodes - Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
ProjectOne - The project is to build a neural network from scratch. The motivation for this project is from nnfs.io a website build by @Sentdex. Nnfs.io is actually meant for a book that teaches the fundamentals of neural network and help us to build our own network. Let's build a new neural network where we can learn the fundamentals and make a great hands-on work space for aspiring machine learning engineers and the GitHub community