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Easy-to-use and general-purpose machine learning in Python
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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 Machine Learning Tools category of a tech stack.
scikit-learn is an open source tool with 58.7K GitHub stars and 25.1K GitHub forks. Here’s a link to scikit-learn's open source repository on GitHub

Who uses scikit-learn?

212 companies reportedly use scikit-learn in their tech stacks, including Delivery Hero, Tokopedia, and RatePAY GmbH.

888 developers on StackShare have stated that they use scikit-learn.

scikit-learn Integrations

Jupyter, Keras, Ludwig, Gradio, and are some of the popular tools that integrate with scikit-learn. Here's a list of all 25 tools that integrate with scikit-learn.
Pros of scikit-learn
Scientific computing
Decisions about scikit-learn

Here are some stack decisions, common use cases and reviews by companies and developers who chose scikit-learn in their tech stack.

Needs advice

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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Needs advice

Should I continue learning Django or take this Spring opportunity? I have been coding in python for about 2 years. I am currently learning Django and I am enjoying it. I also have some knowledge of data science libraries (Pandas, NumPy, scikit-learn, PyTorch). I am currently enhancing my web development and software engineering skills and may shift later into data science since I came from a medical background. The issue is that I am offered now a very trustworthy 9 months program teaching Java/Spring. The graduates of this program work directly in well know tech companies. Although I have been planning to continue with my Python, the other opportunity makes me hesitant since it will put me to work in a specific roadmap with deadlines and mentors. I also found on glassdoor that Spring jobs are way more than Django. Should I apply for this program or continue my journey?

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scikit-learn Alternatives & Comparisons

What are some alternatives to scikit-learn?
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.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.
H2O is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
See all alternatives

scikit-learn's Followers
1112 developers follow scikit-learn to keep up with related blogs and decisions.