Kubeflow
TensorFlow
PyTorch
Keras
Scikit-learn
CUDA
date-fns
Next.js
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
KubeflowBased on our record, NumPy seems to be a lot more popular than Kubeflow. While we know about 107 links to NumPy, we've tracked only 2 mentions of Kubeflow. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I'm David Aronchick - first non-founding PM on Kubernetes, co-founder of Kubeflow [1], and co-founder of the SAME project [2] - and we've spent the past year working on Bacalhau [3], an open source project to bring compute to data. We've recently opened up a public-hosted cluster (all runnable from colab in our docs [4]) and would love your feedback - you can see our vision at the attached blog post. Thanks!... - Source: Hacker News / about 1 year ago
You have GitHub org and a Vue based website up and running already, so it seems like you have tech logistics covered. Just in case it's useful, I have experience with Kubernetes, which can help run computationally intense workloads (even if GPUs are needed) or provide a pool of compute for something like Kubeflow (kubeflow.org). Here if you want, feel free to ignore if you're all covered in this area - I'll be... Source: almost 3 years ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
OpenCV - OpenCV is the world's biggest computer vision library
