ougni Goto Github PK

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

aftershocks_issues

Issues with Deep Learning of Aftershocks by DeVries

ccm-site

NYU PSYCH-GA 3405.002 / DS-GS 3001.006 : Computational cognitive modeling

chiadog

A watch dog providing a peace in mind that your Chia farm is running smoothly 24/7.

datasets

Small Datasets for Quick Prototyping

ddd_gpr

Codes for Causal Inference using GPR

dlaicourse

Notebooks for learning deep learning

dynamic-programming

A collection of interesting dynamic programming problems

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

hmm

HMM Alpha beta recursion and Viterbi

iso-3166-countries-with-regional-codes

ISO 3166-1 country lists merged with their UN Geoscheme regional codes in ready-to-use JSON, XML, CSV data sets

learning-to-learn

Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).

lstm-forecasting

How to use PyTorch LSTMs for time series regression

machinelearningnotebooks

Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft

mlcourse.ai

Open Machine Learning Course

notmnist-to-mnist

A sample of the notMNIST dataset in MNIST format so you can drop new data into your existing MNIST neural nets

pandasql

sqldf for pandas

ptsafall2018

DS-GA 3001.001/.002 Probabilistic time series analysis Fall 2018

qiskit-aqua

Quantum Algorithms & Applications in Python

qiskit-textbook

A university quantum algorithms/computation course supplement based on Qiskit

recession-predictor

Project description: https://medium.com/p/recession-prediction-using-machine-learning-de6eee16ca94?source=email-2adc3d3cd2ed--writer.postDistributed&sk=2f1dab9738769f9658634e61576a08bd

scikit-learn

scikit-learn: machine learning in Python

stock-prediction

texture-vs-shape

Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness" (ICLR 2019 Oral)

timeseries2018

Course page for DS-GA 3001.001 Modeling Time Series Data

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow