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amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

amazon-sagemaker-examples-jp

Japanese translation of Amazon SageMaker Examples and other original sample codes, which will be used in Amazon SageMaker hands-on workshops in Japan.

autogluon

AutoGluon: AutoML for Text, Image, and Tabular Data

baby-steps-of-rl-ja

Pythonで学ぶ強化学習 -入門から実践まで- サンプルコード

backtrader

Python Backtesting library for trading strategies

bert-book

「BERTによる自然言語処理入門: Transformersを使った実践プログラミング」サポートページ

bertviz

Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

cd4ml-scenarios

Repository with sample code and instructions for "Continuous Intelligence" and "Continuous Delivery for Machine Learning: CD4ML" workshops

codesandbox-repository

Created with CodeSandbox

codesandbox-test

Created with CodeSandbox

compfinlecture

Material for Antoine Savine's Computational Finance Lectures at Copenhagen University & Kings College London

csb-jvymrf

deep-analytics-sample

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

gs-quant

Python toolkit for quantitative finance

interpret-text

A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.

kdd20-tutorial

Tutorial on Automated Machine Learning at KDD 2020

keras-rl

Deep Reinforcement Learning for Keras.

ml

nlp-sample

nlp_workshop_odsc_europe20

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models.

notebooks

Implement, demonstrate, reproduce and extend the results of the article 'Differential Machine Learning' (Huge & Savine, 2020), and cover implementation details left out of the working paper

optuna

A hyperparameter optimization framework

python-training

Python training for business analysts and traders

pythonlibs

pytorch101_odsc_europe2020

Beginner workshop on PyTorch - ODSC Europe 2020

redux

Predictable state container for JavaScript apps

resources

A collection of resources for learning and research.

rl_siminar

simple-todo-app