Andrew Reed (andrewrreed)

andrewrreed

Geek Repo

Company:Cloudera Fast Forward Labs

Location:Baltimore, MD

Home Page:https://www.andrewreed.com/

Twitter:@andrewrreed

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Organizations
huggingface

Andrew Reed's repositories

hf-notebooks

Adhoc modeling notebooks for transformer experiments

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data-science-resources

A list of useful blog posts, papers, and websites for all things data science

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cookbook

Open-source AI cookbook

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CML_AMP_Active_Learning

An interactive, visual workflow of active learning using the MNIST dataset.

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CML_AMP_Anomaly_Detection

Apply modern, deep learning techniques for anomaly detection to identify network intrusions.

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CML_AMP_APIv2

Demonstration of how to use the CML API to interact with CML.

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CML_AMP_Canceled_Flight_Prediction

Perform analytics on a large airline dataset with Spark and build an XGBoost model to predict flight cancellations.

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CML_AMP_Churn_Prediction

Build an scikit-learn model to predict churn using customer telco data.

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CML_AMP_Continuous_Model_Monitoring

Demonstration of how to perform continuous model monitoring on CML using Model Metrics and Evidently.ai dashboards

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CML_AMP_Explainability_LIME_SHAP

Learn how to explain ML models using LIME and SHAP.

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CML_AMP_Few-Shot_Text_Classification

Perform topic classification on news articles in several limited-labeled data regimes.

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CML_AMP_Image_Analysis

CML_AMP_Image_Analysis

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CML_AMP_MLFlow_Tracking

Experiment tracking with MLFlow.

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CML_AMP_NeuralQA

CML_AMP_NeuralQA

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CML_AMP_Object_Detection_Inference

Interact with a blog-style Streamlit application to visually unpack the inference workflow of a modern, single-stage object detector.

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CML_AMP_Question_Answering

Explore an emerging NLP capability with WikiQA, an automated question answering system built on top of Wikipedia.

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CML_AMP_SpaCy_Entity_Extraction

A Jupyter notebook demonstrating entity extraction on headlines with SpaCy.

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CML_AMP_Streamlit_on_CML

Demonstration of how to use Streamlit as a CML Application.

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CML_AMP_Summarize

Automatic text summarization with extractive and abstractive models.

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CML_AMP_Tensorboard_on_CML

Demonstration of how to use TensorBoard as a CML Application.

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CML_AMP_Train_Gensim_W2V

Demonstration of how to train Gensim's Word2Vec for a non-language use case.

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gh-issues-scrape

A simple script for scraping issues from Github repositories

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langchain

⚡ Building applications with LLMs through composability ⚡

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notebooks

Notebooks using the Hugging Face libraries 🤗

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Python-for-Algorithms--Data-Structures--and-Interviews

Files for Udemy Course on Algorithms and Data Structures

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train_embeddings_with_gensim

Train Gensim's Word2Vec algorithm to learn item embeddings for downstream tasks such as recommendation systems. Includes techniques for hyperparameter optimization and early stopping.

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