Knet.jl
machine-learning-roadmap
| Knet.jl | machine-learning-roadmap | |
|---|---|---|
| 1 | 5 | |
| 1,418 | 7,164 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | over 1 year ago | |
| Jupyter Notebook | ||
| GNU General Public License v3.0 or later | MIT License |
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.
Knet.jl
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Should you learn Julia or Python for Machine Learning?
We used to use the popular Flux, Knet, MLBase, and Plots packages for Machine Learning in Julia.
machine-learning-roadmap
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Best AI ML DL DS Roadmap
**[Mrdbourke/machine-learning-roadmap on GitHub](https://github.com/mrdbourke/machine-learning-roadmap)**: This GitHub repository is more focused on machine learning. It's a good choice if you're looking for a more community-driven approach, as GitHub repositories often encourage contributions and updates from various experts.
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[D] Best AI ML DL DS Roadmap
Some roadmaps I have found: - [roadmap.sh] AI and Data Scientist Roadmap ← Best? - [i.am.ai] AI Expert Roadmap - [github.com] mrdbourke/machine-learning-roadmap - [github.com] luspr/awesome-ml-courses - [rentry.org] Machine Learning Roadmap
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100+ Must Know Github Repositories For Any Programmer
7. Machine Learning Roadmap
- Where can I start?
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Machine Learning Roadmap
Original article here: https://github.com/mrdbourke/machine-learning-roadmap
What are some alternatives?
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
applied-ml - 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
ThreeBodyBot - Poorly written code that generates moderately exciting plots of a very specific physics phenomenon that enthralls dozens of us around the globe.
stanford-cs-229-machine-learning - VIP cheatsheets for Stanford's CS 229 Machine Learning
edward2 - A simple probabilistic programming language.
interviews.ai - It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
MLBase.jl - A set of functions to support the development of machine learning algorithms
yt-channels-DS-AI-ML-CS - A comprehensive list of 180+ YouTube Channels for Data Science, Data Engineering, Machine Learning, Deep learning, Computer Science, programming, software engineering, etc.
tensorflow - An Open Source Machine Learning Framework for Everyone
Hello-Kaggle - For someone who is new at Kaggle
machine-learning - 🤖 Repository with machine learning algorithms and implementations
awesome-datascience - :memo: An awesome Data Science repository to learn and apply for real world problems.