Showing 36 of 36 projects
An open-source OCR engine that converts images to text, supporting over 100 languages and multiple output formats.
A ready-to-use OCR Python library supporting 80+ languages and popular writing scripts like Latin, Chinese, Arabic, and Cyrillic.
A comprehensive collection of machine learning and deep learning models, trading agents, and simulations for stock market forecasting.
An architecture-free neural network library for Node.js and the browser, supporting various network types.
A friendly JavaScript library that makes machine learning accessible in the browser for artists, creative coders, and students.
A curated list of resources dedicated to recurrent neural networks (RNNs) and deep learning.
A complete AI-driven process using GANs with LSTM and CNN to predict stock price movements, incorporating diverse data sources and hyperparameter optimization.
Human Activity Recognition using TensorFlow and LSTM RNNs on smartphone sensor data to classify six movement types.
Human Activity Recognition using TensorFlow and LSTM RNNs on smartphone sensor data to classify six movement types.
A deep learning framework for training image classification models to solve complex captcha and OCR tasks.
A recurrent neural network that generates classical music using LSTM layers and convolutional-inspired architecture.
A curated collection of high-quality deep learning resources, including courses, books, papers, libraries, and datasets.
Scene text detection using Connectionist Text Proposal Network (CTPN) for detecting text lines in natural images.
A curated list of delightful npm packages that showcase surprising and innovative JavaScript capabilities.
TensorFlow implementation of Neural Turing Machines with LSTM controllers, supporting multiple read/write heads.
A curated collection of research papers on molecular and material design using generative AI and deep learning techniques.
A Recurrent Neural Network library for Torch7's nn, providing RNN, LSTM, GRU, and other sequence modeling modules.
A minimal 200-line implementation of a sequence-to-sequence chatbot using TensorLayer and TensorFlow.
TensorFlow implementation of character-aware neural language models using CNN, highway networks, and LSTM.
Generates realistic handwriting using LSTM Mixture Density Networks implemented in TensorFlow.
A Torch implementation of a VIS+LSTM model for answering questions about images using deep learning.
A PyTorch library for creating and training autoencoders on sequential data (time series, videos, etc.) in just two lines of code.
Deep learning models for crop yield prediction using remote sensing data, with CNN/LSTM and Gaussian Process approaches.
A practical demo using LSTM neural networks with TensorFlow to predict lottery numbers.
A fast neural network framework for iOS and macOS using Swift and Metal for GPU acceleration.
Predicts Bitcoin price trends using an LSTM-RNN with technical indicators for automated trading via the Binance API.
An open-source toolkit for building end-to-end trainable task-oriented dialogue models with neural networks.
A deep learning architecture using stacked residual bidirectional LSTM cells with TensorFlow for human activity recognition from sensor data.
A Clojure library for dynamic neural network graphs with pluggable tensor backends, inspired by PyTorch.
A real-time Bitcoin price prediction system using LSTM models and Twitter sentiment analysis.
A proof-of-concept neural network library in Rust with implementations for MNIST digit recognition and char-rnn LSTM models.
A TensorFlow implementation of neural text generation from structured data, converting tabular information into natural language summaries.
A TensorFlow-based neural network model for generating descriptive captions from images using Flickr30K and MSCOCO datasets.
A machine learning algorithm for accurate, energy-efficient outdoor positioning using 5G mmWave beamformed fingerprints.
A TensorFlow-based model that generates descriptive captions for images using an Inception-v3 encoder and LSTM decoder.
A TensorFlow/Keras LSTM model for hourly weather forecasting, offering univariate, multivariate, and multistep prediction modes.
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