Computer Vision Course By Kaggle
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Updated
Jul 18, 2024 - Jupyter Notebook
Computer Vision Course By Kaggle
带你从零实现一个高性能的深度学习推理库,支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step
American Sign Language (ASL) Detection using CNN
Machine Learning from scratch in C
Some common CUDA kernel implementations (Not the fastest).
Represent trained machine learning models as Pyomo optimization formulations
Evaluate neural network architectures for context-aware next activity prediction
Study of the impact of a Randomized ReLU function on the performance of a neural network model.
This project focuses on identifying the best hyperparameters for modeling and predicting trends in food sales using a Multi-Layer Perceptron (MLP) neural network. The objective is to optimize the MLP model to achieve high predictive accuracy, enabling businesses to make informed decisions regarding inventory management and sales strategies.
Data Science Project: Comparing 3 Deep Learning Methods (CNN, LSTM, and Transfer Learning).
QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch
Neural Network from Scratch using Numpy for MNIST Dataset
Neural Network from Scratch using Numpy for MNIST Dataset
Implementations of neural networks in python for the classification of MNIST datasets.
"The 'Activation Functions' project repository contains implementations of various activation functions commonly used in neural networks. "
identify digits from a dataset of tens of thousands of handwritten images.
Feedforward Neural Network from scratch - backpropagation, gradient descent, activation functions
TorchAct, collection of activation function for PyTorch. https://pypi.org/project/torchact/
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