Unsupervised anomaly detection in vibration signal using PyCaret vs BiLSTM

NLP Named Entity Recognition dalam bidang Biomedis, mendeteksi teks dan membuat klasifikasi apakah teks tersebut mempunyai entitas plant atau disease, memberi label pada teks, menguji hubungan entitas plant dan disease, menilai kecocokan antara kedua entitas, membandingkan hasil uji dengan menggunakan models BERT-BILSTM-CRF

Code and specs for CS-Embed's entry for SemEval-2020 Task-9. We present code-switched embeddings, code for code-switched bilstm sentiment classifier, and code for CS tweet collection.

Personalised fitness recommendation by multi-level deep learning approach.

This project aims to develop a system for automatically extracting emotion-cause pairs from conversational data, enhancing dialogue systems and mental health support through deeper understanding of emotional triggers.

This is the minor-project that is to be submitted to my University, during the 7th semester. We build a BiLSTM model and train the model on textual data - Twitter data.

Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available. Data Set Characteristics: Multivariate, Time-Series. This database have 2,075,259 rows and 7 columns.

Sentiment Analysis on Amazon Reviews using Machine learning models and one deep learning model.

Deep Learning project October 2023

Predict genre of movie from title and description using a Bidirectional LSTM.

Deep learning models and fine-tuned transformers for detecting mental illness from user content on Reddit. 🧠

🚀 Deciphering Customer Sentiments: Harnessing the power of deep learning models such as LSTM and hybrid CNN-LSTM, we've crafted a dynamic Streamlit web app. It turns customer text reviews from Amazon datasets into actionable insights, helping you gauge product quality effortlessly. 📊🌟

The task was to detect fake news regarding COVID-19.

Implemented machine learning across HR, Sales, Marketing, and PR to improve decision-making. Used models like XGBoost, Prophet, LSTM, clustering, and NLP to enhance retention, forecasting, segmentation, and sentiment analysis for business growth.

It's the Repo containing a model for summarization and classification of the Indian legal cases

Predicting sentiment polarity of COVID-19 news articles using Machine Learning and Deep Learning models

Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC) 2020

The code trains an LSTM-based residual model on human motion data and applies transfer learning to detect robotic joint faults. It preprocesses data, maps robot features to human-like patterns, and fine-tunes a model while freezing early layers. The optimized model is evaluated with class weighting, callbacks, and feature importance analysis.

🚀 A hybrid deep learning model for fake news detection using BERT and BiLSTM with attention mechanism.