scikit-learn Reviews & Product Details

I guess this is the library which every newbie who's learning machine learning starts with and so am I. This is a very clean library where you get the basic logical code of many algorithms like regression, classification and clustering etc.As the algorithm is pre written so i only focus on traning the datas and output.It have very clean and smooth API. Review collected by and hosted on G2.com.

As told earlier it is for beginners and if you don't know python then it take you lots of time to understand each thing how it works.It doesn't support heavy models (if you try to make it then it starts to lag and doesn't give desire output).It also have limited customization for the algorithms also,like black boxes and fine grains control is not always easy. Review collected by and hosted on G2.com.

Users who wish to connect the algorithms to their platforms will find detailed API documentation on the scikit-learn website. Many contributors, authors, and a large international online community support and update Scikit-learn. It is easy to use. The library is published under the BSD license, so it is available for free with only the most basic legal and licensing restrictions. The scikit-learn package is extremely adaptable and useful, and can be used for a variety of real-world tasks, such as developing neuroimaging, predicting consumer behavior, etc. Review collected by and hosted on G2.com.

It is not a great choice if one prefers in-depth learning. It provides a simple abstraction that may tempt beginner data scientists to continue without first learning the basics. Review collected by and hosted on G2.com.

I like how dynamic scikit-learn library is. it provides preloaded and ready-to-use functions for all sorts of machine learning and data preprocessing algorithms. Review collected by and hosted on G2.com.

The only downside is the lack of native support for deep learning libraries. Review collected by and hosted on G2.com.

Scikit-learn is built on top of efficient numerical libraries, such as NumPy and SciPy, which provide optimized implementations of mathematical and numerical operations. This ensures that the library can handle large datasets and complex computations efficiently, contributing to its robustness and scalability. Review collected by and hosted on G2.com.

While scikit-learn provides a range of tools for feature selection, extraction, and transformation, it does not offer extensive automated feature engineering capabilities found in some specialized libraries. Users may need to manually engineer or select features based on their domain knowledge or explore other feature engineering libraries or techniques. Review collected by and hosted on G2.com.

The best thing, as per me, is there is documentation available of scikit-learn. So, if I sometimes find it difficult to apply some algorithms, I can check the documentation, which helps me. I like this thing. Scikit-learn also provides many inbuilt datasets so that I can use them for practice purposes. Scikit-learn comes with many machine learning algorithm, which makes easy to me for implementing algorithms. I like that it comes with many data manipulation functions to clean my data according to my requirements. Review collected by and hosted on G2.com.

One thing I don't particularly appreciate is that it doesn't have any Deep Learning algorithms. If I want to develop some production-ready algorithm, then scikit-learn is not so great compared to their competitors. Review collected by and hosted on G2.com.

scikit-learn library is very easy to import and ready to use for the python platform. It also contains some sample datasets for trying machine learning algorithms. Review collected by and hosted on G2.com.

There is as such no point that I dislike in scikit-learn library. Most of the commonly used as well as recent machine learning algorithms are available for use Review collected by and hosted on G2.com.

What I like about Scikitlearn is its documentation, clarity and versatility of the kit. Review collected by and hosted on G2.com.

There's nothing I dislike about it so far. Review collected by and hosted on G2.com.

Informative session and advanced tools for learning Review collected by and hosted on G2.com.

The time duration of the clip should be longer and more detailed. Review collected by and hosted on G2.com.

It is very useful in the beginning for data mining and data analysis. Easy to use. It provides maximum efficiency with minimum effort. Data processing, regression, dimension reduction, classification, cluster analysis are the features I use. It's completely free. Review collected by and hosted on G2.com.

It runs slow on large datasets. It can improve on classification. Review collected by and hosted on G2.com.

I really like it when I solve any Machine learning problem, It has a lot of inbuilt ML models that are tough to implement but here those are easy to use. Review collected by and hosted on G2.com.

I feel that It should have much more good deep Neural network models Review collected by and hosted on G2.com.