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ML in Production - Deployment Series
A multi-part blog series on deploying machine learning models in an automated, reproducible, and auditable manner.
production guide article tutorial
Top Down Introduction to BERT with HuggingFace and PyTorch
I will also provide some intuition into how BERT works with a top down approach (applications to algorithm).
bert top-down huggingface pytorch
DETR: End-to-End Object Detection with Transformers
A new method that views object detection as a direct set prediction problem.
object-detection panoptic-segmentation transformers computer-vision
VirTex: Learning Visual Representations from Textual Annotations
We train CNN+Transformer from scratch from COCO, transfer the CNN to 6 downstream vision tasks, and exceed ImageNet features despite using 10x fewer ...
convolutional-neural-networks transformers coco visual-representations
Model Serving using FastAPI and Streamlit
Simple example of usage of streamlit and FastAPI for ML model serving.
fastapi streamlit deeplabv3 semantic-segmentation
Paraphrase Any Question with T5 (Text-To-Text Transformer)
Given a question, generate paraphrased versions of the question with T5 transformer. Pretrained model and training script provided.
t5 transformers huggingface pytorch
Building Machine Learning Products: A Problem Well-Defined
In this post, we'll dig deeper into how to develop the requirements for a machine learning project when you're given a vague problem to solve.
product-management products systems-design machine-learning
How to Train Your Neural Net
Deep learning for various tasks in the domains of Computer Vision, Natural Language Processing, Time Series Forecasting using PyTorch 1.0+.
pytorch python deep-learning computer-vision
Graph Representation Learning Book
Introduction to graph representation learning, including methods for embedding graph data, graph neural networks, and deep generative models of graphs.
graph-representation-learning graph-neural-networks knowledge-graphs book
AutoGOAL
A Python framework for Automated Machine Learning (AutoML), hyperparameter tunning and program synthesis in general.
automl python machine-learning code
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