How to use docker to train ML Model
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Updated
Nov 11, 2023 - Python
How to use docker to train ML Model
A proof-of-concept for an adaptive sampling method to collect emotions in the wild.
Improving OoD performance of generative models by focusing on the semantic information
A project for MlOps course of ODS
This goal of this repository was to minimize the number of code edits by enabling easy configuration of the Image Classifier pipeline using Hydra, Timm & Lightning.
Autoregressive Neural Networks for accelerating Monte Carlo simulations with quantum data
Experiment with training and tuning convolutional models for person characteristics prediction
This repo contains an implementation of the paper:
Brief but readable implementations to start exploring 3D representation learning techniques in the vein of NeRF.
Point Cloud Segmentation Using PointNet
Domain Adaptation With Domain-Adversarial Training of Neural Networks
Collection of GNN architectures for 3D shapes and graphs using NN Template
Handwriting Synthesis is implemented using PyTorch Lightning by following Alex Grave's paper on sequence generation
Real time facial landmark on CPU Basic CNN model or state of the art model.
Project for the course Deep Learning and Applied AI a.y. 2021/2022, Dept. of Computer Science, Prof. Emanuele Rodolà
A package to aid in building models for RSNA Intracranial Hemorrhage Detection competition
Computer Vision model implementation from scratch
Este repositório contém todos os códigos realizados durante a formação Inteligência Artificial na Data Science Academy. Os códigos foram feitos em Python através do Jupyter Notebook e contém comentários detalhados sobre o passo a passo para uma análise preditiva com Deep Learning.
Example MNIST training using the following MLops tech stack: Ray, PyTorch Lightning, PyTorch, MLflow and Python 3.10.12.
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