Reweight GPT - a simple neural network using transformer architecture for next character prediction
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Updated
Aug 28, 2023 - Jupyter Notebook
Reweight GPT - a simple neural network using transformer architecture for next character prediction
This is a cross-chip platform collection of operators and a unified neural network library.
wind turbine fault detection based on machine learning techniques and knowledge transfer
Recommender System (Hybrid and Deep Neural Networks)
Interactive Voice Recognition Windows Application (Pending Newer Revisions)
A little toolbox for training a deep learning model or machine learning model
this repo for begineers who just start learning a deep learning concept , this is the easy way implementation of the model by useing an customer churn predication dataset from kaggle,must refer for begineers in deep leaniing
This repository will talk about the most powerful ML/DL model in AI industry
A snake game to be played manually or to be tested against a neural network algorithm. The neural network is configurable on the ui. Extended statistics about game data can be provided via webserver interface. Additionally, a demo mode with a trained neural network is implemented.
Laboratory assignments given during the Computational NeuroScience(CNS) course. University of Pisa. A.Y. 2023/2024
Collection of AI projects that I've worked on. This is mainly used for learning projects.
Implemented diverse neural network concepts including image classification, kNN, SVM, and advanced techniques like convolutional nets and style transfer for image processing and analysis. Experimented with architectures, regularization methods, and applications such as image captioning and generation.
动手学强化学习_进阶篇_代码复现_Deep_Q-Learning
Computer vision
Recurrent Neural Network implementation for gold price trend forecasting using LSTM layers and time series analysis in Python
Exploratory Data Analysis, Data Visualization, Machine Learning
Exploring machine learning through captivating projects. 🚀🤖
A deep learning based DNA sequence analysis project using an attention model to localize statistically unusual mutations.
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