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annotated_deep_learning_paper_implementations

🧑‍🏫 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit), optimizers (adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, etc. 🧠

awesome-jmeter

A collection of resources covering different aspects of JMeter usage.

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

bayesian_marketing_attribution

Marketing attribution using bayesian credible sets and regression methods

blogs

boston_housing

chatbot_ner

chatbot_ner: Named Entity Recognition for chatbots.

co-learning-lounge

Welcome to the one point community-driven encyclopedia for anything in technology.

crewai-examples

cs231n

Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

cs7280_network_science

customer-segmentation

Applying unsupervised Kmeans algorithm

cvat

Powerful and efficient Computer Vision Annotation Tool (CVAT)

d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.

d3-book

Code examples for “Interactive Data Visualization for the Web”

datapane

Datapane is the easiest way to create data science reports from Python.

deep-learning-for-recommendation-systems

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

deepface

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

deeplearning

dex

OpenID Connect Identity (OIDC) and OAuth 2.0 Provider with Pluggable Connectors

eda-for-conversion-rate-dataset

fastapi-azure-auth

Easy and secure implementation of Azure AD for your FastAPI APIs 🔒 B2C, single- and multi-tenant support.

fastbook

Draft of the fastai book

finding_donors

Finding Donors Udacity Machine Learning Project Submission

gam-coach

Personal coach to help you obtain desired AI decisions!

grape

🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations

hanhan_data_science_resources2

more data science resources

introstatlearn

Exercises from 'Introduction to Statistical Learning with Applications in R' written in Python.

introtoml-udacity

Identifying the conspirators in Enron fraud using Email Data

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code