5921 Open source projects that are alternatives of or similar to Libfm_in_keras

高速でJuliaを学ぶ入門チュートリアル

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Methods with examples for Feature Selection during Pre-processing in Machine Learning.

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Simple package that makes your generator work in background thread

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An educational AI robot based on NVIDIA Jetson Nano.

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A wrapper of the COCOeval class for extended keypoint error estimation analysis.

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U-Net implementation in Tensorflow

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Juliabox continues to run, but this codebase is no longer current.

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Entity linking framework

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Remove problematic gender bias from word embeddings.

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A DCGAN that generate Cat pictures 🐱‍💻

Open sourced research notebooks by the QuantConnect team.

This repository contains Ipython notebooks of assignments and tutorials used in the course introduction to data science in python, part of Applied Data Science using Python Specialization from University of Michigan offered by Coursera

Mask R-CNN for Pulmonary Nodules Diagnosis, using TensorFlow 天池医疗AI大赛：Mask R-CNN肺部结节智能检测（Segmentation + Classification）

Example code from the book "Deep Learning for the Life Sciences"

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TF2.0 / TensorFlow 2.0 / TensorFlow2.0 官方文档中文版

A simple NLP library allows profiling datasets with one or more text columns. When given a dataset and a column name containing text data, NLP Profiler will return either high-level insights or low-level/granular statistical information about the text in that column.

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코딩셰프의 3분 딥러닝, 케라스맛

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The BIGGAN based Anime generation implemented with tensorflow. All training data has been open sourced.

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Machine Learning for Finance, published by Packt

Kotlin API for Lets-Plot - an open-source plotting library for statistical data.

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1st place solution for the Kuaishou Active-user Forecast competition

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This is Andrew NG Coursera Handwritten Notes.

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AI/ML citation graph with postgres + graphql

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A S3 backed ContentsManager implementation for Jupyter

supercell

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该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

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Quantitative Interview Preparation Guide, updated version here ==>

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Anomaly detection for temporal data using LSTMs