mlpack VS examples

Compare mlpack vs examples and see what are their differences.

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mlpack examples
4 147
4,909 7,851
1.1% 0.6%
9.9 4.0
2 days ago 5 days ago
C++ Jupyter Notebook
GNU General Public License v3.0 or later Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

mlpack

Posts with mentions or reviews of mlpack. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-23.
  • How much C++ is used when it comes to performing quant research?
    1 project | /r/quant | 3 Jul 2023
    Does C++ have the equivalent of Pandas or Apache Spark? Are there extensive libraries that exist/are being developed that allow you to perform operations with data? Or do people just use a combination of Python & its various libraries (NumPy etc)? If we leave aside the data bit, are there libraries that allow you to develop ML models in C++ (mlpack for instance ) faster & more efficiently compared to their Python counterparts (scikit-learn)? On a more general note, how does C++ fit into the routine of a Quant Researcher? And at what scale does an organization decide they need to start switching to other languages and spend more time developing the code ?
  • What is the most used library for AI in C++ ?
    3 projects | /r/cpp_questions | 23 Jan 2022
    mlpack is a great library for machine learning in C++. It's very fast and not too much of a learning curve.
  • Ensmallen: A C++ Library for Efficient Numerical Optimization
    3 projects | news.ycombinator.com | 8 Dec 2021
    This toolkit was originally part of the mlpack machine learning library (https://github.com/mlpack/mlpack) before it was split out into a separate, standalone effort.
  • Top 10 Python Libraries for Machine Learning
    14 projects | dev.to | 9 Sep 2021
    Github Repository: https://github.com/mlpack/mlpack Developed By: Community, supported by Georgia Institute of technology Primary purpose: Multiple ML Models and Algorithms

examples

Posts with mentions or reviews of examples. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-07-01.
  • AI Tools for Developers in 2024
    2 projects | dev.to | 1 Jul 2024
    TensorFlow
  • Essential Deep Learning Checklist: Best Practices Unveiled
    20 projects | dev.to | 17 Jun 2024
    How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include functionality to log predictions and consider parallel processing or GPU utilization for speed enhancements.
  • Mathematics secret behind AI on Digit Recognition
    3 projects | dev.to | 15 Jun 2024
    Hi everyone! I’m devloker, and today I’m excited to share a project I’ve been working on: a digit recognition system implemented using pure math functions in Python. This project aims to help beginners grasp the mathematics behind AI and digit recognition without relying on high-level libraries like TensorFlow or PyTorch. You can find the complete code on my GitHub repository.
  • Awesome List
    25 projects | dev.to | 8 Jun 2024
    TensorFlow - An end-to-end open source machine learning platform. TensorFlow Documentation - Tutorials and documentation.
  • My Favorite DevTools to Build AI/ML Applications!
    9 projects | dev.to | 23 Apr 2024
    TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
  • Open Source Ascendant: The Transformation of Software Development in 2024
    4 projects | dev.to | 19 Mar 2024
    AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
  • Best AI Tools for Students Learning Development and Engineering
    2 projects | dev.to | 18 Mar 2024
    Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
  • Releasing The Force Of Machine Learning: A Novice’s Guide 😃
    3 projects | dev.to | 22 Feb 2024
    TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
  • MLOps in practice: building and deploying a machine learning app
    2 projects | dev.to | 11 Jan 2024
    The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
  • 🔥14 Excellent Open-source Projects for Developers😎
    5 projects | dev.to | 10 Dec 2023
    10. TensorFlow - Make Machine Learning Work for You 🤖

What are some alternatives?

When comparing mlpack and examples you can also consider the following projects:

Dlib - A toolkit for making real world machine learning and data analysis applications in C++

cppflow - Run TensorFlow models in C++ without installation and without Bazel

tensorflow - An Open Source Machine Learning Framework for Everyone

awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!

SHOGUN - Shōgun

face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

xgboost - 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, Dask, Flink and DataFlow

Selenium WebDriver - A browser automation framework and ecosystem.

Caffe - Caffe: a fast open framework for deep learning.

Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing

mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
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Did you konow that C++ is
the 6th most popular programming language
based on number of metions?