AI-Expert-Roadmap
tensorflow
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| AI-Expert-Roadmap | tensorflow | |
|---|---|---|
| 30 | 221 | |
| 28,388 | 182,323 | |
| 1.6% | 0.7% | |
| 0.0 | 10.0 | |
| 4 months ago | 6 days ago | |
| JavaScript | C++ | |
| MIT License | Apache License 2.0 |
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.
AI-Expert-Roadmap
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Best AI ML DL DS Roadmap
**[I.am.ai AI Expert Roadmap](https://i.am.ai/roadmap)**: This roadmap focuses more on AI and includes various aspects of machine learning and deep learning. It's suitable for those who want to delve deeper into AI, particularly in cutting-edge research and applications.
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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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[D] Roadmap.sh vs Al Expert Roadmap
[i.am.ai] AI Expert Roadmap
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Suggest which roadmap should I follow for ML?
1.https://i.am.ai/roadmap
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Where can I start?
I recommend this site where there's a roadmap for becoming an AI expert: https://i.am.ai/roadmap
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Can some one suggest Top certification courses for AI ?
Currently, I'm also learning about AI from this source https://github.com/AMAI-GmbH/AI-Expert-Roadmap
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How to study Machine Learning effectively?
I suggest following this roadmap. You might be put off by the amount of statistics topics, but it truly underpins almost all of machine learning so it's definitely useful to know.
- Como meterme al mundo AI
- Aprender IA siendo Programador?
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Mlops roadmap
Also: https://i.am.ai/roadmap/
tensorflow
- 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? :)
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How to do deep learning with Caffe?
You can use Tensorflow's deep learning API for this.
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When the documentation has TODOs
Since you've specifically mentioned ML, here's Tenserflow's GitHub. I'm sure a quick glance through that will change your mind.
What are some alternatives?
developer-roadmap - Interactive roadmaps, guides and other educational content to help developers grow in their careers.
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）
cryptocurrency-price-prediction - Cryptocurrency Price Prediction Using LSTM neural network
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
dalle-playground - A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini)
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
igel - a delightful machine learning tool that allows you to train, test, and use models without writing code
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.
arbitrary-image-stylization-tfjs - Arbitrary style transfer using TensorFlow.js
scikit-learn - scikit-learn: machine learning in Python
LeetCode - This is my LeetCode solutions for all 2000+ problems, mainly written in C++ or Python.
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.