Software Alternatives, Accelerators & Startups

Public.com VS Scikit-learn

Compare Public.com VS Scikit-learn and see what are their differences

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Public.com logo Public.com

Buy any stock with any amount of money. Commission-free.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Public.com Landing page
    Landing page //
    2023-10-01
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Public.com

Website
public.com
$ Details
-
Release Date
2018 January
Startup details
Country
United States
State
New York
City
New York
Founder(s)
Jannick Malling
Employees
250 - 499

Public.com features and specs

  • Commission-Free Trading
    Public.com offers commission-free trading, which means users can buy and sell stocks without incurring transaction fees, making investing more accessible.
  • Social Investing Platform
    The platform integrates social media elements that allow users to follow other investors, share insights, and discover new investment opportunities through a community-driven approach.
  • Fractional Shares
    Public.com enables users to purchase fractional shares, which allows for diversification even with smaller amounts of capital by buying portions of expensive stocks.
  • Educational Resources
    Public.com offers various educational tools and resources designed to help new investors learn the basics of investing and make informed decisions.

Possible disadvantages of Public.com

  • Limited Investment Options
    Compared to some other platforms, Public.com has a more limited range of investment options, as it primarily focuses on stocks and ETFs, lacking features for options or futures trading.
  • Lack of Advanced Trading Tools
    The platform is not geared towards advanced traders as it lacks sophisticated trading tools and charting capabilities that are available on some other platforms.
  • No Retirement Accounts
    Public.com does not offer retirement accounts such as IRAs, which may be a disadvantage for users looking to invest specifically for retirement.
  • Social Features Overload
    For those who prefer a straightforward investing experience, the social aspects of Public.com could be seen as distractions from the main goal of investing.

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Analysis of Scikit-learn

Overall verdict

  • Yes, Scikit-learn is generally regarded as a good library for machine learning, especially for beginners and intermediate users who need reliable tools with efficient implementation of numerous algorithms.

Why this product is good

  • Scikit-learn is considered a good machine learning library because it provides a wide range of state-of-the-art algorithms for supervised and unsupervised learning. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. The library is well-documented, easy to use, and has a consistent API that simplifies the integration of different algorithms. Furthermore, there's a strong community and continuous development, which means it is well-maintained and updated regularly with new features and improvements.

Recommended for

  • Beginners learning machine learning concepts and application.
  • Data scientists and engineers looking for a robust and efficient toolkit to build and deploy machine learning models.
  • Researchers who need an easy-to-use library that facilitates the experimentation of various algorithms.
  • Developers who require a seamless, Python-based machine learning library that integrates well with other data analysis tools and environments.

Public.com videos

Public.com Review | UP TO $300 FREE STOCK | Walkthrough | Pros/Cons

More videos:

  • Review - Public.com Review 2021 | Features, Pros & Cons

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Category Popularity

0-100% (relative to Public.com and Scikit-learn)
Investing
100 100%
0% 0
Data Science And Machine Learning
Finance
100 100%
0% 0
Data Science Tools
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 Public.com and Scikit-learn

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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...

Social recommendations and mentions

Public.com might be a bit more popular than Scikit-learn. We know about 47 links to it since March 2021 and only 40 links to Scikit-learn. 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.

Public.com mentions (47)

  • I reached $10,000 in savings for the first time in my life.
    Another vote for treasuriesโ€ฆ theyโ€™re paying 5.4% atm! I found the treasury.gov site to be super clunky and opted to buy my treasuries (6m short-terms) through Public. Itโ€™s been nice to drip any extra money here and there and it definitely adds up fast. Source: about 3 years ago
  • Possible to earn 4-5% on bond/cash-like assets
    HL allow you to buy bonds, and public.com is another major site. Source: over 3 years ago
  • Welcome to the Official Public Subreddit
    Follow the Public.com community guidelines found here - Failure to comply with these guidelines may result in a temporary or permanent ban. Source: over 3 years ago
  • What's the best trading platform except public.com?
    Unfortunately, public.com is region locked to the USA. Its unavailable in my country, so I'm asking for an alternative. Because Glizzlord has been saying that other trading platforms have bad business models and or steal information and sell it, I'm afraid to pick one on my own. Could the interested in stocks here suggest me a platform to start on? Source: over 3 years ago
  • We the Investors Partners.
    Public.com is an app based brokerage- Open To the Public Investments, Inc, that has existed under numerous names for twenty years or so. Public uses Apex for it's clearing house, they put GME and others onto PCO as a result, during the sneeze. They were, purportedly angry about it. They also stepped back from PFOF as of 2/16/21.... Just after the sneeze. And probably just to get out from the shitstorm of hate... Source: almost 4 years ago
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Scikit-learn mentions (40)

  • Detecting Ingress Tool Transfer (T1105) with Python
    Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / 3 months ago
  • Best AI Cybersecurity Training for Security Teams: How to Pick
    Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / 3 months ago
  • Where to Get Hands-On AI Training for Cybersecurity Professionals
    Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 3 months ago
  • How Anomaly Detection Actually Works in Security Operations
    Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 4 months ago
  • Building a Personalized Meal Recommendation System
    In practice, youโ€™ll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 6 months ago
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What are some alternatives?

When comparing Public.com and Scikit-learn, you can also consider the following products

Robinhood - Free stock trading service.

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

TradingView - The best charting tool for crypto and stocks

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

Crypto Price Tracker - An app for all your cryptocurrency needs!

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