Visualizer for neural network, deep learning and machine learning models

《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

Code samples for my book "Neural Networks and Deep Learning"

Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js

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

A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values

Deep and online learning with spiking neural networks in Python

Deep learning in Rust, with shape checked tensors and neural networks

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

This repository contains small projects related to Neural Networks and Deep Learning in general. Subjects are closely linekd with articles I publish on Medium. I encourage you both to read as well as to check how the code works in the action.

NVIDIA DLSS is a new and improved deep learning neural network that boosts frame rates and generates beautiful, sharp images for your games

Another Chinese Translation of Neural Networks and Deep Learning

java deep learning algorithms and deep neural networks with gpu acceleration

Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.

The repository contains script and notebook related to Statistics, Machine learning, Neural network, Deep learning, NLP, Numerical methods, and Automation.

Books related to Artificial Intelligence, Machine Learning, Deep Learning and Neural Networks

Code from the "Tensorflow and deep learning - without a PhD, Part 2" session on Recurrent Neural Networks.

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516

In this paper, we apply machine learning to create bots for Halite III, @twosigma's annual A.I. competition. We develop one classifier using Support Vector Machine with Supervised Learning, and one using a Deep Neural Network with Reinforcement Learning

This is my assignment on Andrew Ng's course “neural networks and deep learning”

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A framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning

Awesome Deep Learning for Time-Series Imputation, including an unmissable paper and tool list about applying neural networks to impute incomplete time series containing NaN missing values/data

CAI NEURAL API - Pascal based deep learning neural network API optimized for AVX, AVX2 and AVX512 instruction sets plus OpenCL capable devices including AMD, Intel and NVIDIA.

NUS CS5242 Neural Networks and Deep Learning, Xavier Bresson, 2025

Hands-on, practical knowledge of how to use neural networks and deep learning with Keras 2.0

The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks