6692 Open source projects that are alternatives of or similar to Deeplearning.ai Natural Language Processing Specialization

Plain python implementations of basic machine learning algorithms

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Deep Learning Specialization by Andrew Ng on Coursera.

Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.

该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

A neural network that transforms a design mock-up into a static website.

Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]

Implementation of a seq2seq model for summarization of textual data. Demonstrated on amazon reviews, github issues and news articles.

Using LSTM or Transformer to solve Image Captioning in Pytorch

📃 **Unofficial** PyTorch Implementation of DA-RNN (arXiv:1704.02971)

Codes for weekly challenges on Deep Learning by Siraj

Python code for common Machine Learning Algorithms

RadIO is a library for data science research of computed tomography imaging

Coherent Semantic Attention for image inpainting(ICCV 2019)

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

A clear, concise, simple yet powerful and efficient API for deep learning.

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Implementation of a seq2seq model for Speech Recognition using the latest version of TensorFlow. Architecture similar to Listen, Attend and Spell.

links to conference publications in graph-based deep learning

Applying Data Science and Machine Learning to Solve Real World Business Problems

Quiz & Assignment of Coursera

Complete Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"

Probabilistic reasoning and statistical analysis in TensorFlow

（完结）网易云课堂微专业《深度学习工程师》听课笔记，编程作业和课后练习

Action recognition using soft attention based deep recurrent neural networks

Deep learning codes and projects using Python

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

My personal notes, presentations, and notebooks on everything Deep Learning.

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

Machine Learning notebooks for refreshing concepts.

Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)

[电影推荐系统] Based on the movie scoring data set, the movie recommendation system is built with FM and LR as the core(基于爬取的电影评分数据集，构建以FM和LR为核心的电影推荐系统).

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

quizzes/assignments for mathematics for machine learning specialization on coursera

Implementation of "Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning"

Transformer of "Attention Is All You Need" (Vaswani et al. 2017) by Chainer.

Grokking Deep Reinforcement Learning

Machine Learning Practical course repository

AI for everyone! 🎉 Neural networks, tools and a library we use in Supervisely

Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"

Contains my explorations of TensorFlow 2.x

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Repo for the Deep Reinforcement Learning Nanodegree program

An open-source tool for sequence learning in NLP built on TensorFlow.

Keras tutorial for beginners (using TF backend)

BERT for Multitask Learning

My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT pretrained models.

由淺入深的深度學習資源 Collection of deep learning materials for everyone

This is Andrew NG Coursera Handwritten Notes.

吴恩达机器学习coursera课程，学习代码(2017年秋) The Stanford Coursera course on MachineLearning with Andrew Ng