Top 23 Python Numpy Projects
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
data science ipython notebooks
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Now we can see that the numpy library has been added to the packages. That way we can install the libraries and packages required for the project.
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Scout APM
Scout APM: A developer's best friend. Try free for 14-days. Scout APM uses tracing logic that ties bottlenecks to source code so you know the exact line of code causing performance issues and can get back to building a great product faster.
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datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Project mention: Hugging Face Introduces ‘Datasets’: A Lightweight Community Library For Natural Language Processing (NLP) | reddit.com/r/artificial | 2021-11-08Code for https://arxiv.org/abs/2109.02846 found: https://github.com/huggingface/datasets
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Project mention: How to load 85.6 GB of XML data into a dataframe | reddit.com/r/pythontips | 2021-12-01
I’m quite sure dask helps and has a pandas like api though will use disk and not just RAM.
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Project mention: Can anyone recommend resources to prepare for Pandas and Numpy interview questions? | reddit.com/r/datascience | 2021-09-24
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if you have just a few methods that need to be sped up, you could also consider Numba
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Project mention: [D] Paper Explained - Sparse is Enough in Scaling Transformers (aka Terraformer) | Video Walkthrough | reddit.com/r/MachineLearning | 2021-12-01
Code: https://github.com/google/trax/blob/master/trax/examples/Terraformer_from_scratch.ipynb
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Fast Array Manipulation in Python: Since Numpy is the de facto standard for storing multi-dimensional data, any performance gain you see using librapid math kernels will need to be realized on data which probably started its life as a numpy array, and needs to be passed to another tool as a numpy array. Hopefully there will be (or already is?) a way to build a librapid array out of a numpy array without copying the data and vice versa. In fact I might suggest that librapid focus on the fast math operations and simply become an accelerator for numpy arrays. For instance, look at CuPy which provides GPU-implemented operations within a numpy-compatible API, and Bottleneck which simply provides fast C-based implementations of some otherwise slow parts of Numpy. Also note that numpy *can* be multi-threaded depending on the operation and some environment variables. Single-threaded to Single-threaded I think you will be hard-pressed to beat Numpy on general math operations, but that doesn't mean there aren't specific "kernels" that are more specialized that can be greatly improved with a C++ back-end.
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This should get you back to a more intuitive understanding: https://github.com/arogozhnikov/einops It don't reshape/flatten/reduce without it now. I'd advise that you take the time to read and practice along the tutorial.
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"On the simpler side". Do you mean with a graphical interface? Then, orange would be a nice solution. https://orangedatamining.com/
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Project mention: We built a pi controlled hydroponics box that grows your plants 1.5x faster using ML | reddit.com/r/raspberry_pi | 2021-04-26
but it looks like none of your plants are supported by the plantvillage model, or do I understand something wrong? https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/image_classification/plant_village.py#L57
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Project mention: Rust is slow (in ways that matter to the most people) | reddit.com/r/rustjerk | 2021-10-23
A great example is orjson, which is faster and more correct than equivalent libraries written in C.
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mars
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
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numpyro
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Perhaps an alternative to look into: Numpyro [1] has a JAX backend so can be really fast when compiled; and it can run on GPUs. So that might be helpful for your problem with loads of data.
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There are also online & offline onset detection approaches available as part of the Python madmom library https://github.com/CPJKU/madmom as binaries and Python classes. The methods included in madmom have shown state of the art results in multiple Music Information Retrieval Evaluation eXchange (MIREX) campaigns in recent years. Hope that's useful to you.
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Project mention: How to write a resume for python / ML jobs? | reddit.com/r/learnmachinelearning | 2021-02-06
my most useful project is yolo object detector implementation in tf2 and I'm currently working on 2 other projects, one of which is the implementation of various drl algorithms in tf and the other project will be based on the latter and it's concerned with trading. The rest are more of scripts rather than projects ex: web scraping, file management, programming challenges ...
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GeneticAlgorithmPython
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Project mention: PyGAD 2.16.1 Released: An open-source Python library for building the genetic algorithm and optimizing machine learning models. | reddit.com/r/learnmachinelearning | 2021-09-29The user can use the tqdm library to show a progress bar. https://github.com/ahmedfgad/GeneticAlgorithmPython/discussions/50
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Project mention: Change docstring style for a project's entire codebase | reddit.com/r/pycharm | 2021-05-17
Ah - I was thrown off by 'type' vs 'style'. You might want to take a look at https://github.com/dadadel/pyment
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Re: Matchering (https://github.com/sergree/matchering), here is a little more information. If I recall correctly there is a docker-ized version so you can run it locally relatively easily if you are willing to learn a couple of bash commands. I have not played with it a lot and it is separate from the DAW.
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Project mention: [P] Fastest wavelet transforms in Python + synchrosqueezing | reddit.com/r/MachineLearning | 2021-05-05
Also see Kymatio for SOTA on timeseries with limited data, fast and differentiable; nice lecture.
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PySR
Simple, fast, and parallelized symbolic regression in Python/Julia via regularized evolution and simulated annealing
Project mention: [D] Inferring general physical laws from observations in 300 lines of code | reddit.com/r/MachineLearning | 2021-08-02This is really neat! Since you're interested in this subject, you may also appreciate PySR and the corresponding paper which uses Graph Neural Networks to perform symbolic regression.
Python Numpy related posts
- [D] Paper Explained - Sparse is Enough in Scaling Transformers (aka Terraformer) | Video Walkthrough
- How to load 85.6 GB of XML data into a dataframe
- How to load 85.6 GB of XML data into a dataframe
- Virtual Environments Python
- 11 Malicious PyPI Python Libraries Caught Stealing Discord Tokens and Installing Shells
- Writing entire programs in Cython
- Benchmarking the Apple M1 Max
Index
What are some of the best open-source Numpy projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | data-science-ipython-notebooks | 21,875 |
| 2 | NumPy | 18,946 |
| 3 | datasets | 11,444 |
| 4 | Dask | 9,239 |
| 5 | numpy-100 | 7,541 |
| 6 | Numba | 7,039 |
| 7 | trax | 6,611 |
| 8 | cupy | 5,568 |
| 9 | einops | 3,914 |
| 10 | orange | 3,108 |
| 11 | datasets | 3,072 |
| 12 | orjson | 2,538 |
| 13 | xarray | 2,324 |
| 14 | mars | 2,288 |
| 15 | numpyro | 1,186 |
| 16 | Eliot | 929 |
| 17 | madmom | 828 |
| 18 | yolo-tf2 | 721 |
| 19 | GeneticAlgorithmPython | 711 |
| 20 | pyment | 670 |
| 21 | matchering | 509 |
| 22 | kymatio | 472 |
| 23 | PySR | 443 |
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