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scikit-learn
Byscikit-learnscikit-learn

scikit-learn

#6in Development & Training Tools
Stacks1.26kDiscussions7
Followers1.14k
OverviewDiscussions7

What is scikit-learn?

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

scikit-learn is a tool in the Development & Training Tools category of a tech stack.

scikit-learn Pros & Cons

Pros of scikit-learn

  • ✓Scientific computing
  • ✓Easy

Cons of scikit-learn

  • ✗Limited

scikit-learn Alternatives & Comparisons

What are some alternatives to scikit-learn?

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

CUDA

CUDA

A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.

Streamlit

Streamlit

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

Torch

Torch

It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

scikit-learn Integrations

Xcessiv, Keras, Ludwig, Cortex.dev, Jupyter and 7 more are some of the popular tools that integrate with scikit-learn. Here's a list of all 12 tools that integrate with scikit-learn.

Xcessiv
Xcessiv
Keras
Keras
Ludwig
Ludwig
Cortex.dev
Cortex.dev
Jupyter
Jupyter
AutoMLPipeline
AutoMLPipeline
baikal
baikal
Yellowbrick
Yellowbrick
Hummingbird
Hummingbird
Jovian
Jovian
cnvrg.io
cnvrg.io
Gradio
Gradio

scikit-learn Discussions

Discover why developers choose scikit-learn. Read real-world technical decisions and stack choices from the StackShare community.Showing 1 of 5 discussions.

DraftedDev
DraftedDev

Mar 2, 2023

Needs adviceonTensorFlowTensorFlowNumPyNumPyscikit-learnscikit-learn

Hi, I wanted to jump into Machine Learning.

I first tried brain.js, but its capabilities are very limited and it abstracts most concepts of ML away. I've tried TensorFlow, but it's very hard for me to understand the concepts.

Now, I thought about trying NumPy or scikit-learn, but I don't really know much about ML, but still want to use 100% Power of ML.

What do you recommend me to use as a beginner in ML?

Also do you know any good tutorials which explain how ML works and how to implement it in a given framework (ideal in german)?

Thanks for your attention & help :D

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