tensorflow
developer-roadmap
tensorflow | developer-roadmap | |
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223 | 2,112 | |
182,575 | 275,643 | |
0.5% | - | |
10.0 | 9.8 | |
2 days ago | 4 days ago | |
C++ | TypeScript | |
Apache License 2.0 | 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.
tensorflow
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Side Quest Devblog #1: These Fakes are getting Deep
# L2-normalize the encoding tensors image_encoding = tf.math.l2_normalize(image_encoding, axis=1) audio_encoding = tf.math.l2_normalize(audio_encoding, axis=1) # Find euclidean distance between image_encoding and audio_encoding # Essentially trying to detect if the face is saying the audio # Will return nan without the 1e-12 offset due to https://github.com/tensorflow/tensorflow/issues/12071 d = tf.norm((image_encoding - audio_encoding) + 1e-12, ord='euclidean', axis=1, keepdims=True) discriminator = keras.Model(inputs=[image_input, audio_input], outputs=[d], name="discriminator")
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Google lays off its Python team
[3]: https://github.com/tensorflow/tensorflow/graphs/contributors
- TensorFlow-metal on Apple Mac is junk for training
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
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10 Github repositories to achieve Python mastery
Explore here.
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GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
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Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
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Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
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Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
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
✅ 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?
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
C++ Workflow - C++ Parallel Computing and Asynchronous Networking Framework
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
freeCodeCamp - freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
data-engineer-roadmap - Roadmap to becoming a data engineer in 2021
scikit-learn - scikit-learn: machine learning in Python
substrate - Substrate: The platform for blockchain innovators
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
system-design-primer - Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.