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bostonhousingprice

creditcard_fraud_detection_with_ann

Credit card fraud detection model on imbalanced dataset using weighted neural network with Keras

fake-news-detection-using-lstm-blstm

Implemented LSTM and BLSTM-based fake news detection model to preprocess textual data with 90.85% accuracy

google_mediapipe

machine-learning

machine-learning-graphs

Matplotlib graphs, graphs using Pandas dataframes, and Plotly

nlp

point-of-sale

predictive_modelling

Utilized Decision Tree, Random Forest, Gradient Boosting, SVC, and AdaBoost to predict student placement. Created Linear Regression, Random Forest, and XGBoost models to predict car prices with 6% mean absolute error

rna_dna_sequencing

sentiment_analysis

Implemented pre-trained Transformer-based distilBERT and BERT multilingual model to classify sentiments in positive or negative class and ranked them on scale of 1 to 5

sql

transferlearning_vgg16-

Evaluated pre-trained VGG16 classification model on flower dataset to get 97.37% accuracy, and built VGG16 model from scratch with early stopping to get 76% accuracy.

voice-activated-search-bot-for-wikipedia-and-youtube

Voice bot using speech recognition and python text-to-speech libraries which searched text on Wikipedia and YouTube based on specific word commands

youtube_video_title_sentiment_analysis

YouTube Trending Video data-set which gets updated daily. Dataset is available on Kaggle: https://www.kaggle.com/datasets/rsrishav/youtube-trending-video-dataset/data