cnn-lstm-models

Here are 32 public repositories matching this topic...

Pradnya1208 / Time-series-forecasting-using-Deep-Learning

The goal of this notebook is to implement and compare different approaches to predict item-level sales at different store locations.

deep-learning time-series tensorflow cnn lstm-model lstm-neural-networks time-series-forecasting cnn-lstm-models

Updated Jan 11, 2022
Jupyter Notebook

abhilash1910 / Deep_Reinforcement_Learning_Trading

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Deep Reinforcement Learning for Trading

Updated Oct 10, 2022
Jupyter Notebook

Jithsaavvy / Deploying-an-end-to-end-keyword-spotting-model-into-cloud-server-by-integrating-CI-CD-pipeline

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The project is a concoction of research (audio signal processing, keyword spotting, ASR), development (audio data processing, deep neural network training, evaluation) and deployment (building model artifacts, web app development, docker, cloud PaaS) by integrating CI/CD pipelines with automated tests and releases.

docker flask deep-neural-networks ci-cd python3 deeplearning asr heroku-deployment kws mlops mlflow dockercontainers github-actions tensorflow2 cnn-lstm-models mlops-workflow mlops-project

Updated Sep 4, 2022
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Mark-THU / load-point-forecast

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load point forecast

deep-neural-networks transformer lstm gru cnn-model mlp-networks seq2seq-attn load-forecasting cnn-lstm-models

Updated Jan 24, 2022
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LuluW8071 / Automatic-Speech-Recognition-with-PyTorch

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Real-Time ASR with CNN-BiLSTM: End-to-End Live Streaming Using PyTorch Lightning⚡

python deep-neural-networks pytorch cuda-support kenlm asr-model cnn-lstm-models pytorch-lightning ctc-decode

Updated Jan 23, 2025
Python

Jason-Oleana / image-to-sequence-prediction

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The goal is to learn to generate the Scalable Vector Graphics (SVG) code correspondig to images of simple colored shapes. SVG is a markup language which is used to define vector graphics.

image-captioning cnn-lstm cnn-lstm-models

Updated Feb 23, 2024
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nithinsoundar / Retail-Demand-Forecasting

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A deep learning model that predicts the demand of an item for a particular time period in 10 retail stores. The model showed an RMSE of 18. Various deep learning models such as CNN, LSTM, MLP, CNN-LSTM were compared and CNN-LSTM showed the least RMSE.

deep-learning mlp cnn-model lstm-neural-networks cnn-lstm-models

Updated Jan 28, 2023
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niravnb / Deep-learning-projects

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computer-vision deep-learning sentiment-analysis random-forest chatbot word-embeddings text-generation xgboost image-classification ensemble-learning image-captioning autoencoders nlp-machine-learning cnn-architecture time-series-forecasting lstm-sentiment-analysis cnn-lstm-models

Updated Dec 15, 2019
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codiceSpaghetti / VoiceVibes

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VoiceVibes presents a solution for speech emotion recognition, featuring six innovative AI model architectures designed to accurately categorize emotional expressions conveyed through speech.

genetic-algorithm ensemble-learning speech-emotion-recognition cnn-lstm-models stacking-ensemble

Updated Jan 31, 2023
Jupyter Notebook

aaaastark / hybrid-model-with-cnn-lstm-python

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Hybrid Model with CNN and LSTM for VMD dataset using Python

python data-science machine-learning deep-learning tensorflow numpy sklearn keras pandas vmd lstm-model matplotlib cnn-keras cnn-model hybrid-model cnn-architecture cnn-classification lstm-neural-network cnn-lstm-models

Updated Oct 12, 2022

joyeetadey / Violence-Detection-From-Videos

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realtime violence detection from videos using cnn-lstm model

convolutional-neural-networks vgg16 sequential-models violence-detection video-augmentation resnet101 cnn-lstm-models violence-data

Updated Jan 13, 2022
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DeeThunder / Electrical-Faults-Analysis---Classification

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Hybrid CNN-LSTM deep learning model for electrical fault classification in power transmission lines. Achieves 78% accuracy across 6 fault types using time-series analysis. Includes complete ML pipeline with preprocessing, training, and evaluation tools. Built with TensorFlow & Keras.

python data-science machine-learning deep-learning tensorflow signal-processing keras neural-networks convolutional-neural-networks power-systems hybrid-model time-series-analysis fault-detection predictive-maintenance transmission-lines cnn-lstm-models fault-classification

Updated Feb 14, 2026
Python

yasty-sanchez / ADHD_fMRI_DL

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This project uses CNN and CNN-LSTM models to classify ADHD from fMRI data, using pretrained weights from a CNN autoencoder (CNN-AE) for better feature extraction.

pytorch autoencoder adhd cnn-classification fmri-data cnn-lstm-models