Software Alternatives & Reviews

Scikit-learn VS Backtrader

Compare Scikit-learn VS Backtrader and see what are their differences

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Backtrader logo Backtrader

Backtrader is a complete and advanced python framework that is used for backtesting and trading.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Backtrader Landing page
    Landing page //
    2021-09-30

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Backtrader videos

Backtrader Python Review

More videos:

  • Review - Algorithmic Trading with Python and Backtrader (Part 1)
  • Review - Backtrader Live Forex Trading with Interactive Brokers (Part 1)

Category Popularity

0-100% (relative to Scikit-learn and Backtrader)
Data Science And Machine Learning
Finance
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Development
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Scikit-learn and Backtrader

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Backtrader Reviews

We have no reviews of Backtrader yet.
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Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Backtrader. It has been mentiond 27 times since March 2021. 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.

Scikit-learn mentions (27)

  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
View more

Backtrader mentions (3)

  • My reality of trading and how i wish i had never started.
    I do like what I see and hear about backtrader.com. I would say they are a notable exception to my general rule of not trusting or using backtesting frameworks. However, I still think it is important to understand how the framework you are using works. So if you are using backtrader for backtesting you still need to put in the time to understand the backtesting engine. Source: about 1 year ago
  • My reality of trading and how i wish i had never started.
    What about backtrader.com? And I feel like it would be step 2 after you at least have something to backtrade and test haha. Source: about 1 year ago
  • I need to know what can go wrong with my 'masterplan'
    Backtesting is basically applying your strategy on historical price data to see if it makes money. I've used Backtrader it works decently well: https://backtrader.com/. Source: over 2 years ago

What are some alternatives?

When comparing Scikit-learn and Backtrader, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

QuantConnect - QuantConnect provides a free algorithm backtesting tool and financial data so engineers can design algorithmic trading strategies. We are democratizing algorithm trading technology to empower investors.

OpenCV - OpenCV is the world's biggest computer vision library

quantra - A public API for quantitative finance made with Quantlib

NumPy - NumPy is the fundamental package for scientific computing with Python

Streak.world - Streak.world is one of the leading algo trading platforms, allowing you to design an algorithm to automate your trading strategies without any coding skills needed.