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A portable, offline-first CLI AI assistant built with C++ and llama.cpp. Features dynamic file context awareness, memory management, and runs entirely from a USB drive without dependencies.
This project predicts the next day's stock closing price using Lag Features + Linear Regression (with scikit-learn). Built with public financial data from Yahoo Finance and visualized with cost convergence and prediction analysis.
This project is a simple sequence-to-sequence (seq2seq) neural machine translation model built using TensorFlow. It translates English sentences into Spanish using LSTM-based encoder-decoder architecture. The dataset used is the spa-eng parallel corpus, which consists of thousands of sentence pairs.
This Project Predicts/Forecast Next Day's Temperature By Using RNN.It compares ARIMA and RNN models on real-world time series data from Melbourne, Australia. The goal is to build accurate and generalizable temperature predictors using Python and TensorFlow.
Repositories
9A portable, offline-first CLI AI assistant built with C++ and llama.cpp. Features dynamic file context awareness, memory management, and runs entirely from a USB drive without dependencies.
This project predicts the next day's stock closing price using Lag Features + Linear Regression (with scikit-learn). Built with public financial data from Yahoo Finance and visualized with cost convergence and prediction analysis.
This project is a simple sequence-to-sequence (seq2seq) neural machine translation model built using TensorFlow. It translates English sentences into Spanish using LSTM-based encoder-decoder architecture. The dataset used is the spa-eng parallel corpus, which consists of thousands of sentence pairs.
This Project Predicts/Forecast Next Day's Temperature By Using RNN.It compares ARIMA and RNN models on real-world time series data from Melbourne, Australia. The goal is to build accurate and generalizable temperature predictors using Python and TensorFlow.
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