Cryptocurrency prediction using LSTM (Long Short Term Memory)
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Updated
Jun 3, 2024 - Jupyter Notebook
Cryptocurrency prediction using LSTM (Long Short Term Memory)
Deep convolutional and LSTM feature extraction approach with 784 features.
This project involves developing a machine learning model to predict user preferences in chatbot conversations, using a dataset of head-to-head responses from various large language models. The goal is to enhance chatbot-human interactions by aligning chatbot responses more closely with human preferences.
Gathers deep learning models for Stock forecasting including trading bots and simulations
An LSTM model that can predict the closing price of a stock.
Students Engagement Detection Using Hybrid EfficientNetB7 Together With TCN, LSTM, and Bi-LSTM (DAiSEE and VRESEE datasets)
基于LSTM针对长时序的气温、降水、气压、相对湿度、风速等气象站点数据,对尼洋河径流进行模拟预测
All Assignments of the course, Statistical Methods in AI at IIITH, Monsoon 2024
testing MLP, DQN, PPO, SAC, policy-gradient by snake
Tesseract Open Source OCR Engine (main repository)
Gathers deep learning models for Stock forecasting including trading bots and simulations
Emotion Classifier Model
Project aims to forecast potato prices in India using LSTM, KNN, and Random Forest Regression, integrating historical data on prices, regional stats, and rainfall patterns. Targeting agricultural stakeholders for informed decision-making.
BSP 2 - Housing Market Dynamics: Exploratory Analysis and Future Behavior Forecasting
Utilizing LSTM Neural Networks to forecast energy cosumption trends with time series analysis. Employing Collaborative Filtering with Matrix Factorization and SVD, the system suggests personalized actions based on user behavior, fostering energy conservation.Leveraging Isolation Forest to detect anomalies in consumption patterns.
This repository contains a collection of time series forecasting models, including: Statistical Models Simple and robust models that leverage statistical techniques to forecast future values.
scripts used for neural decoding of single and multi unit auditory cortex data
Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.
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