applied-ml
TheAlgorithms
applied-ml | TheAlgorithms | |
---|---|---|
13 | 62 | |
25,984 | 179,812 | |
- | 1.5% | |
3.0 | 9.7 | |
5 days ago | 3 days ago | |
Python | ||
MIT License | 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.
applied-ml
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[D] Favorite ML Youtube Channels/Blogs/Newsletters
Also, have any of you stumbled across any cool GitHub repos like this one: https://github.com/eugeneyan/applied-ml ?
- Curated Papers on Machine Learning in Production
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Top Github repo trends in 2021
The second repo I LOVE is Eugene Yan’s Applied ML repository. This is a brilliant idea to create and actually something I was planning on sort of casually doing in my non-existent free time… Anyhow, it is a curated list of technical posts from top engineering teams (Netflix, Amazon, Pinterest, Linkedin, etc.) detailing how they built out different types of AI/ML systems (e.g. forecasting, recommenders, search and ranking, etc.). Ofc, it focuses on AI/ML, but something similar could be made for the traditional or BI-oriented analytics stack, as well as the streaming world, super high value for practitioners! Btw-one of my favorite things at BCG used to be looking at our IT architecture team’s reference architecture diagrams… the best way to understand technologies is to look at how a ton of stuff is architected… and its fun!
- Curated papers, articles, & blogs on data science and ML in production
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Messed up my career by pivoting to DS. Wondering if it's too late to switch to MLE
Applied ML: A collection of papers, articles, and blogs on ML in production by different companies (Netflix, Uber, Facebook, LinkedIn, etc)
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[D] A dilemma of an ML guy in industry
Eugene Yan's applied-ml has tons of case studies.
- Papers & tech blogs by companies sharing their work on data science & machine learning in production.
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My information dump for people trying to break into data science/interview notes
https://github.com/eugeneyan/applied-ml You may find some of his links interesting. I would avoid anything that refers to scaling up a platform as these are more backend engr focus. The more relevant posts to you are probably on the scale of blog posts that are product oriented like the ones I listed in section 4 (e.g. we wanted to solve X for our users and this is how we scoped and defined it). The technical aspects should come backseat to the business aspects. There's def a lot of companies/blog posts that he missed, but the internet is huge.
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[D] Can anyone point me to resources/case studies of companies/business creating infrastructure for their data needs?
Check the resources mentioned in applied-ml. It includes blog posts/papers from many companies describing how they built some ML product X.
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What content would be useful to intermediate Data Scientist
Check out this repo. They collect hundreds of case studies, broken down by dozens of methodologies from large real-world companies such as AirBnB, Nvidia, Uber, Netflix etc.
TheAlgorithms
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Top 10 GitHub Repositories for Python and Java Developers
3. TheAlgorithms/Python - For those interested in algorithms and data structures, this repository offers Python implementations for a wide range of algorithms. It's a great way to deepen understanding of algorithmic learning with Python. https://github.com/TheAlgorithms/Python
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Wikifunctions
Is it me or does it not seem very well thought out? Every example I've seen only has implementations in JavaScript and/or Python. I haven't seen any other languages nor a way to search by language. What a "string" means in one language can be completely different in another language. The primitive data types that the project assumes are not really supported across all programming languages.
Also if anyone hasn't already seen them, similar projects already exist and are more complete. E.g.
* https://rosettacode.org/
* https://programming-idioms.org/
* https://the-algorithms.com/
Not to mention LeetCode, CodeWars, Project Euler, Exercism can kinda serve the same role.
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Introduction
Hey Everyone, My name is Rachit Chawla and Its my first blog on dev.to. I am currently a student of Computer Programming and Analysis at Seneca College. Also I'm currently on my co-op term working as an Automation Developer at Ontario Public Service. In this role, I am currently working with PowerShell scripting and Microsoft Azure for automating every manual tasks to reduce workload and increase efficiency. This blog is a part of OSD600 course at Seneca College. I am taking this course as I am big fan of open source and always wanted to contribute in open source projects but I am unaware of proper documentation and standards used for open source contributions. I am hoping to learn all the required stuff by the end of this course and I aim to be one of the 15k contributors to Linux's repo by Linus Torvald. Open Source interests me because it gives developers the power to customise the application they want to use, also a chance to help others and improve their skills. I found https://github.com/TheAlgorithms/Python interesting from the Monthly trending feed on Github as it has all the algorithms which help us improve time complexity and write better codes. I has about 1000 contributors which helped to code all the algorithms in Python which may help others for working or learning purposes. I myself was a student of Data Structures and Algorithms in Python Winter 2023 and hoping to even able to contribute to this repo itself, once I learn more about documentation & proper standards to be followed.
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I am studying my college Python so can I learn algorithms from it?
The Algorithms Contains many open source implementations of algorithms. Check it out.
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Where To Read About Python Algos?
If you want to see implementations of all possible traversal algorithms you can find it here.
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Book of pythonic code
The mother load of all algorithms in python is here. dfs/bfs in particular are in the graph section.
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Any tips to improve my coding abilites ?
There is no one way to learn all these but here are some resources: 1. Gooking algorithms [https://edu.anarcho-copy.org/Algorithm/grokking-algorithms-illustrated-programmers-curious.pdf\] 2. Algorithms in all languages [https://the-algorithms.com/] 3. Node js best practices. [https://github.com/goldbergyoni/nodebestpractices] 4. Refactoring [https://refactoring.guru/] 5. Learn about Clean Code and Clean Architecture from uncle bob. https://www.youtube.com/watch?v=NeXQEJNWO5w&ab_channel=StreamAConStreamingConferences
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Self taught developers: where are you in your journey?
DSA basics
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Algo and data structures
I would recommend The Algorithms, it comes with descriptions and examples in multiple programming languages.
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A site that hosts implementations of various programming algorithms in different languages
There's also The Algorithms. Many implementations are unfortunately low quality. The Lua ones (disclaimer: I wrote them) should be fine however.
What are some alternatives?
awesome-mlops - A curated list of references for MLOps
new-world-fishing-bot - user friendly python script who is able to catch fish in the game New World
awesome-ml-blogs - Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps
python-ds - No non-sense and no BS repo for how data structure code should be in Python - simple and elegant.
machine-learning-roadmap - A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
python-patterns - A collection of design patterns/idioms in Python
Cookbook - The Data Engineering Cookbook
algorithms
ml-surveys - đź“‹ Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
more-itertools - More routines for operating on iterables, beyond itertools
pipebase - data integration framework
ClointFusion - Cloint India Pvt. Ltd's (ClointFusion) Pythonic RPA (Automation) Platform