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

add statistical annotations (pvalue significance) on an existing boxplot generated by seaborn boxplot

PyTorch implementation of Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

Running parametric t-SNE by Laurens Van Der Maaten with Octave and oct2py.

A collection of notebook to learn the Applied Predictive Modeling using Python.

Implementation of Statistical Learning Method, Second Edition.《统计学习方法》第二版，算法实现。

Tutorial on "Modern Optimization Methods in Python"

PyTorch implementation of Tacotron speech synthesis model.

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python's design philosophy emphasizes code readability with its notable use of significant white space. (This repository contains Python 3 Code)

전 세계의 멋진 케라스 문서 및 튜토리얼을 한글화하여 케라스x코리아를 널리널리 이롭게합니다.

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

A crash course in six episodes for software developers who want to become machine learning practitioners.

Installations for Data Science. Anaconda, RStudio, Spark, TensorFlow, AWS (Amazon Web Services).

A python package that includes many methods for decoding neural activity

PyTorch Implementation of Focal Loss and Lovasz-Softmax Loss

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

Python solutions to solve practical business problems.

Automatic Music Transcription with Deep Neural Networks

《统计学习方法》（第一版）习题解答，在线阅读地址：https://datawhalechina.github.io/statistical-learning-method-solutions-manual

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

Code and Dataset for CVPR2020 "Dynamic Refinement Network for Oriented and Densely Packed Object Detection"

Easy to use Python camera interface for NVIDIA Jetson

Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers

Code for our paper "Hamiltonian Neural Networks"

Machine Learning and Deep Learning Resources

A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)

Exploration of methods for coloring t-SNE.

SuperComputing 2017 Deep Learning Tutorial

AWS Retail Demo Store is a sample retail web application and workshop platform demonstrating how AWS infrastructure and services can be used to build compelling customer experiences for eCommerce, retail, and digital marketing use-cases

Jupyter notebooks associated with the Algorithms for Optimization textbook

Python version of Quantiacs toolbox and sample trading strategies

Ray tutorials from Anyscale

Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller

Jupyter notebooks and other materials developed for the Columbia course APMA 4300

Deep fusion project of deeply-fused nets, and the study on the connection to ensembling

Exercises for the Analysis of Knowledge Graphs

Code to synthesise textures using convolutional neural networks as described in Gatys et al. 2015 (http://arxiv.org/abs/1505.07376)

CNN image style transfer 🎨.

Code and examples for JHU Computational Genomics class

exercise for nndl

A PyTorch implementation of PointRend: Image Segmentation as Rendering

从零基础开始机器学习之旅

Detect text in natural images with SSD, Single Shot Detection

Use the Mask RCNN for the human pose estimation

Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program

Transfer learning for music classification and regression tasks

Python Bootcamp docs and lectures (UC Berkeley)

Source code accompanying: BigQuery: The Definitive Guide by Lakshmanan & Tigani to be published by O'Reilly Media

Food detection and recommendation with deep learning

主要存储Datawhale组队学习中“编程、数据结构与算法”方向的资料。

Create delightful python projects using Jupyter Notebooks

Practical Exercise Codes for PyTorch

Estimates the size of a PyTorch model in memory

Kernel Density Estimation in Python

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

Scientific Python Geometric Algorithms Library