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amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

anomalize

Tidy anomaly detection

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

autogluon

AutoGluon: AutoML for Text, Image, and Tabular Data

autoxgb

XGBoost + Optuna

aws-data-wrangler

Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

aws-shell

An integrated shell for working with the AWS CLI.

bootstrap-npm-starter

Starter template for new Bootstrap-powered npm projects.

cifar100_imagerecognition

CIFAR-100 Image Recognition Using Convolutional Neural Network

colabcode

Run VSCode (codeserver) on Google Colab or Kaggle Notebooks

cppcoreguidelines

The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++

cs50p-edx

Intro Python CS50P

cs50p-project

CS50P Final Project. Introduction to Programming with Python

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

data-visualization

datasets

TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

fashionmnist-pytorch

FashionMnist-Pytorch

free_r_tips

Free R-Tips is a FREE Newsletter provided by Business Science. It comes with bite-sized code tutorials every Tuesday.

git-secrets

Prevents you from committing secrets and credentials into git repositories

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

intro

Project5

it-cert-automation-practice

Google IT Automation with Python Professional Certificate - Practice files

lab

Repo test lab

learnopencv

Learn OpenCV : C++ and Python Examples

lets-build-something-live

lstm-sentiment-analysis

Sentiment Analysis with LSTMs in Tensorflow

machine-learning-links-and-lessons-learned

List of all the lessons learned, best practices, and links from my time studying machine learning

march-madness-ml

Machine learned bracketology