6352 Open source projects that are alternatives of or similar to Pylbm

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

基于ltp的简单评论观点抽取模块

nbconflux converts Jupyter Notebooks to Atlassian Confluence pages

A collection of examples for the ML.NET machine learning package from Microsoft

It is the DKT+ model implemented in python3 and tensorflow1.2

The Biggest Scala Cheat-Sheet.

Implementing YOLO using ResNet as the feature extraction network

Neural reparameterization improves structural optimization

Amazon SageMaker examples for prebuilt framework mode containers, a.k.a. Script Mode, and more (BYO containers and models etc.)

introduction to text analytics in python training for odsc west 2018

Robust Object Classification of Occluded Objects in Forward Looking Infrared (FLIR) Cameras

A short tutorial for Torchtext, the NLP-specific add-on for Pytorch.

Embed strange attractors using a regularizer for autoencoders

Voice Conversion using Cycle GAN's For Non-Parallel Data

Code for the paper "Controlling Style and Semantics in Weakly-Supervised Image Generation", ECCV 2020

Resources for Machine Learning Pocket Reference

http://zeroviscosity.com/category/d3-js-step-by-step

This repository includes the code used in my corresponding Medium post.

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

🔮 GraphQL error management made Easy, generate custom machine-readable errors for Apollo Client/Server from the CLI

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

Interactive guide to Auclert, Bardóczy, Rognlie, and Straub (2019): "Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models".

Code & Data for Introduction to Machine Learning with Scikit-Learn

Série histórica dos dados sobre COVID-19, a partir de informações do Ministério da Saúde

推荐系统从入门到实战

SegNet-Basic with Keras

statistics and classes for exploratory spatial data analysis

CS231n 2019年春季学期课程作业

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

Deep Learning: Image classification, feature visualization and transfer learning with Keras

Python package for publishing Jupyter Notebooks as Medium blogposts

Kaggle Toxic Comments Challenge

图像检索和向量搜索，similarity learning,compare deep metric and deep-hashing applying in image retrieval

This is the code for "Quantum Machine Learning LIVE" By Siraj Raval on Youtube

R package to interface with OpenML

Local AI demo and distributed AI demo using TensorFlow

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

Public repo for Materials API documentation

Export Spotify playlists using the Web API. Analyze them in the Jupyter notebook.

My repository for the Carvana Image Masking Challenge

ISMIR 2020 Tutorial for Metric Learning in MIR

Assets for data8.org

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

Neural machine translator for English2German translation.

A set of Jupyter notebooks demonstrating collaborative filtering using matrix factorization with Keras.

Computational reproducibility using Continuous Integration to produce verifiable end-to-end runs of scientific analysis.

TensorFlow Tutorials with YouTube Videos

Python scripts that supplement the Coursera Computational Neuroscience course by the University of Washington

Video2GIF neural network model from our paper at CVPR2016

[Book-2019] Pragmatic AI: An Introduction to Cloud-based Machine Learning

A Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the different algorithms works and their differents caracteristics.

Code for "Online and Linear Time Attention by Enforcing Monotonic Alignments"

This is the code for "How to Generate Video - Intro to Deep Learning #15' by Siraj Raval on YouTube