Andrew-NG-Notes VS Note

Compare Andrew-NG-Notes vs Note and see what are their differences.

Note

Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, Gemma, CLIP, ViT, ConvNeXt, Segformer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow. (by NoteDance)
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Andrew-NG-Notes Note
1 48
2,266 35
- -
0.0 9.9
2 months ago 3 days ago
Jupyter Notebook Python
- Apache License 2.0
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Andrew-NG-Notes

Posts with mentions or reviews of Andrew-NG-Notes. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-18.

Note

Posts with mentions or reviews of Note. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Andrew-NG-Notes and Note you can also consider the following projects:

Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes

deep-RL-trading - playing idealized trading games with deep reinforcement learning

machine_learning_complete - A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.

deep-significance - Enabling easy statistical significance testing for deep neural networks.

gdrl - Grokking Deep Reinforcement Learning

softlearning - Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

fsdl-text-recognizer-2022-labs - Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022

quickai - QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

DeepNeuralNetworksFromScratch - Different kinds of deep neural networks (DNNs) implemented from scratch using Python and NumPy, with a TensorFlow-like object-oriented API.

muzero-general - MuZero

strategy-ml-nn - This example shows how to use neural networks for writing a trading system on stocks.

cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)