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NumPy Alternatives
Similar projects and alternatives to NumPy
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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Nim
Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
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InfluxDB
Purpose built for real-time analytics at any scale. InfluxDB Platform is powered by columnar analytics, optimized for cost-efficient storage, and built with open data standards.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better NumPy alternative or higher similarity.
NumPy discussion
NumPy reviews and mentions
Posts with mentions or reviews of NumPy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-08-20.
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Streamlit 101: The fundamentals of a Python data app
It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”
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A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
The OpenCV image is a regular NumPy array. You can see it shape:
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Useful Python Libraries for AI/ML
pandas - The standard data analysis and manipulation tool numpy - scientific computing library seaborn - statistical data visualization sklearn - basic machine learning and predictive analysis CausalML - a suite of uplift modeling and causal inference methods PyTorch - professional deep learning framework PivotTablejs - Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook LazyPredict - build and work with and compare multiple models phidata - Build AI Assistants with memory, knowledge and tools. Lux - automates visualization and data analysis pycaret - low-code machine learning library. really nice Cleanlab - for when you are working with messy data drawdata - draw a dataset from inside Jupyter pyforest - lazy import popular data science libs streamlit - simple ui builder, useful for demonstrating ML results
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Python: From Beginners to Pro in 30 Mins (Part 1)
PyCharm also integrates well with various Python frameworks and tools. It offers excellent support for web development frameworks like Django and Flask and scientific computing libraries like NumPy and Matplotlib.
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Pi calculation world record with over 202T digits
>That section is recommended but not required for a conforming implementation:
Who cares? The C standard for math.h requires these functions to be present as specified. They are specified to round correctly, the C standard specifies them to be present as specified, therefore the C standard specifies them as present and correctly rounded. I literally quoted the relevant sections, there are no conforming C specification which give different results.
>Hyperbolic tan is in the list of recommended functions, and yet: https://github.com/numpy/numpy/issues/9187
Any evidence whatsoever that this is caused by two differing implementations of tanh, which BOTH conform to the IEEE 754 standard?
Everyone is free to write their own tanh, it is totally irrelevant what numpy gives, unless there are calls to two standard confirming tanh function which for the same datatype produce different results.
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Beating NumPy matrix multiplication in 150 lines of C
Doesn’t numpy have runtime SIMD dispatching and whatnot based on CPU flags?
E.g. https://github.com/numpy/numpy/blob/main/numpy/_core/src/com...
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Your Weekly Dive into Programming, Web3, and Open-Source Tools
Numpy: Just release version2
- NumPy 2.0.0 release – first major release since 2006
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Essential Deep Learning Checklist: Best Practices Unveiled
How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include functionality to log predictions and consider parallel processing or GPU utilization for speed enhancements.
- NumPy 2.0.0 Release Notes
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A note from our sponsor - InfluxDB
www.influxdata.com | 10 Sep 2024
Stats
Basic NumPy repo stats
291
27,480
10.0
5 days ago
numpy/numpy is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of NumPy is Python.
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