applied-ml
developer-roadmap
applied-ml | developer-roadmap | |
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13 | 2,112 | |
25,984 | 275,643 | |
- | - | |
3.0 | 9.8 | |
5 days ago | 4 days ago | |
TypeScript | ||
MIT License | GNU General Public License v3.0 or later |
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.
developer-roadmap
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How to start learning web development for free
Learning the basics of web development opens doors to many other careers in the tech field. Roadmap.sh provides guides, learning paths, and roadmaps to point developers in a direction of their choosing.
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5 Uncommon Advices from one beginner coder to another beginner coder!
There's a website I personally follow specific for roadmaps called as “roadmap.sh” where all the roadmaps are available. You can check it out, if you like. Here's the link: ▶️ https://roadmap.sh/
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Programming vs Web Development
If you're starting your journey in web development, here is a roadmap to follow. Understand that Web development is not merely an extension of programming; it's a distinct field that requires a unique blend of coding and visual design skills. Embrace the importance of visual aesthetics from the get-go, and continuously work on improving your design sense. Trust me it will pay off in the long run, and you'll be able to create truly exceptional web experiences that not only function well but also look and feel amazing.
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Developer should-know websites
Github developer roadmaps (backend, frontend, cloud ...)
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Unique websites for the Developer - TechGenieDev
Roadmap.sh (https://roadmap.sh/)
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Top 10 GitHub Repositories Every Web Developer Should Know
Web Developer-Roadmap GitHub Link: developer-roadmap Crafted by kamranahmedse, this roadmap acts as a compass for developers navigating the vast landscape of technologies. Covering front-end, back-end, and DevOps, it aids developers in charting a learning path aligned with their goals.
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10 GitHub repositories that every developer must follow
âś… kamranahmedse/developer-roadmap: https://github.com/kamranahmedse/developer-roadmap
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ChatGPT as a Programming Mentor: A Test Drive
It may also be beneficial to start with a high-level overview of what there is to learn in a given area, to understand the overall lay of the land - and then use ChatGPT to dig deeper into selected topics. There are many good resources that provide such an overview, like roadmap.sh or my "Definitive Guide to Succeeding as a Professional Dev".
- 18 Must-Bookmark GitHub Repositories Every Developer Should Know
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Resources I wish I knew when I started my career
5. Roadmap
What are some alternatives?
awesome-mlops - A curated list of references for MLOps
C++ Workflow - C++ Parallel Computing and Asynchronous Networking Framework
awesome-ml-blogs - Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
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.
freeCodeCamp - freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.
Cookbook - The Data Engineering Cookbook
data-engineer-roadmap - Roadmap to becoming a data engineer in 2021
ml-surveys - đź“‹ Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
substrate - Substrate: The platform for blockchain innovators
pipebase - data integration framework
system-design-primer - Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.