Deeplearning4j
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation. (by deeplearning4j)
| Deeplearning4j | kaggle-environments | |
|---|---|---|
| 13 | 55 | |
| 13,427 | 273 | |
| 0.3% | 0.0% | |
| 5.8 | 6.4 | |
| 7 days ago | 3 days ago | |
| Java | Jupyter Notebook | |
| Apache License 2.0 | 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.
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.
Deeplearning4j
Posts with mentions or reviews of Deeplearning4j.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-29.
- Deeplearning4j Suite Overview
- Java for ML?
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Best way to combine Python and Java?
Have you considered migrating off of Python to just using JVM ML libraries then? I hear good things about Deeplearning4j, but there's quite a few.
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Anybody here using Java for machine learning?
I've gone to the linux workflow as directed in the docs and reconstructed the maven command line:
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Data Science Competition
DL4J
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Java Matrix Benchmark is Updated! See how linear algebra libraries compare for speed
Hey folks, just letting you know we see this thread and I appreciate you guys running these benchmarks. I'm not seeing any of your posts on our forums. I think I saw a notification from our examples but we do not actually monitor that. Please use: https://community.konduit.ai/ or at least the main repo dl4j issues: https://github.com/eclipse/deeplearning4j/issues and you'll get a lot more visibility. Thanks!
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Does Java has similar project like this one in C#? (ml, data)
Also, the website is now redirected to: https://deeplearning4j.konduit.ai/
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If it gets better w age, will java become compatible for machine learning and data science?
On top of this several popular projects have been built. This includes tensorflow-java and our project eclipse deeplearning4j: https://github.com/eclipse/deeplearning4j
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Matrices multiplication benchmark: Apache math vs colt vs ejml vs la4j vs nd4j
Nd4j is actively developed. The latest commit was 6 hours ago. Nd4j is part of deeplearning4j which is now owned by eclipse (but the main contributors are from a company) https://github.com/eclipse/deeplearning4j/tree/master/nd4j
kaggle-environments
Posts with mentions or reviews of kaggle-environments.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-27.
- Data Science Roadmap with Free Study Material
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Help needed! My first hackathon
If you are interested in Data Science, you may want to look at Kaggle competitions. https://www.kaggle.com/competitions
- What's a statistical / research methodology, that's not usually taught in grad programs, that you think more IO's should be aware about?
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Freaking out about how I’m inexperienced to land an internship and eventually a job
Secondly, if you feel like you do not have enough skills or a lack of practice answering problem statements, there are a lot of good websites where you can find interesting projects. I would recommend starting participating in some Kaggle competitions or download some free Google datasets and start playing with them.
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Capitalism provides half-assed solutions to extinction-level problems caused by capitalism
For reference: Kaggle is a Google product. You can see the list of current competitions here.
- Where can neural networks take me? - Semi-existential crisis
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What Can I Do With My Time as a Substitute for Strategy Computer Games?
You could try Kaggle competitions, or participating in forecasting markets (as you stated) is another option. You don't need any specific skill set to be a forecaster, the rules of the bet are stipulated and from there it's just based on your ability to predict the outcome. You could also try your hand at investing in the stock market, or try and make money betting on sports games. If you're very good at this stuff I'm sure you can make a lot of money doing it. The thing to keep in mind is that generally video games are much much easier than real life
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What is the best advanced professional certification for Data Science/ML/DL/MLOps?
As to the specifics of your projects, that's up to you. Try browsing Kaggle; check out some of the work we have on The Pudding; check out some journalism examples to see what you can try to build on or improve.
- Suggestions for projects on kaggle for cv?
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Hi! Im doing research on AI innovation. Does anybody know any specific platform where I can learn/understand and get case studies or on-going projects that companies are implementing? Thanks for your help!
You might want to look at kaggle competitions.
What are some alternatives?
When comparing Deeplearning4j and kaggle-environments you can also consider the following projects:
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
CKAN - CKAN is an open-source DMS (data management system) for powering data hubs and data portals. CKAN makes it easy to publish, share and use data. It powers catalog.data.gov, open.canada.ca/data, data.humdata.org among many other sites.
Weka
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
tensorflow - An Open Source Machine Learning Framework for Everyone
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Smile - Statistical Machine Intelligence & Learning Engine
docarray - Represent, send, store and search multimodal data
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
datasci-ctf - A capture-the-flag exercise based on data analysis challenges
Apache Mahout - Mirror of Apache Mahout
dremio-oss - Dremio - the missing link in modern data
Deeplearning4j vs Deep Java Library (DJL)
kaggle-environments vs CKAN
Deeplearning4j vs Weka
kaggle-environments vs stable-baselines
Deeplearning4j vs tensorflow
kaggle-environments vs stable-baselines3
Deeplearning4j vs Smile
kaggle-environments vs docarray
Deeplearning4j vs Pytorch
kaggle-environments vs datasci-ctf
Deeplearning4j vs Apache Mahout
kaggle-environments vs dremio-oss