6716 Open source projects that are alternatives of or similar to Deepnlp Models Pytorch

Lecture slides, Jupyter notebooks, and other material from the LSSTC Data Science Fellowship Program

The WeightWatcher tool for predicting the accuracy of Deep Neural Networks

Tutorial: Web scraping in Python with Beautiful Soup

This repository contains my python (3) script examples that focus on use cases for Network Engineers.

How to do Unsupervised Clustering with Keras

Researches for Natural Language Processing for Financial Domain

Tools, wrappers, etc... for data science with a concentration on text processing

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Apache Spark (PySpark) Practice on Real Data

Notes and Summaries on ML-related Research Papers (with optional implementations)

Ropsten public testnet PoW chain

朱小五写文章涉及到的数据分析，爬虫，源数据

w-net: a convolutional neural network architecture for the self-supervised learning of depthmap from pairs of stereo images.

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".

NeMo: a toolkit for conversational AI

(Part of) Chris Albon's Machine Learning with Python Cookbook in .ipynb form

The Language Interpretability Tool: Interactively analyze NLP models for model understanding in an extensible and framework agnostic interface.

retrain gpt-2 in colab

[DEPRECATED] An IPython notebook-compatible Javascript/HTML viewer for matplotlib animations

Convolutional neural network analysis for predicting DNA sequence activity.

Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

Observations and notes to understand the workings of neural network models and other thought experiments using Tensorflow

General Assembly's Data Science course in Washington, DC

メディカルAIコース オンライン講義資料

🍔

Decentralized Machine Learning Client

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

책) 파이썬으로 데이터 주무르기 - 소스코드 및 데이터 공개

Multi-Graph Convolutional Neural Networks

Simple Encoder, Generator and Face Modificator with StyleGAN2

The accompanying files for the book 'Dataviz with Python and JavaScript'

💎 数学公式识别

RadIO is a library for data science research of computed tomography imaging

This trading-gym is the first trading for agent to train with episode of short term trading itself.

Data Visualization with Python

Intro to deep learning for medical imaging lesson, by MD.ai

Go binding for TensorFlow Lite

Full Stack Data Science in Python

Python for Finance Cookbook, published by Packt

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection.

Quick, visual, principled introduction to pytorch code through five colab notebooks.

This is a tutorial for PyTorch Geometric on the YooChoose dataset

我的强化学习笔记和学习材料📖 still updating ... ...

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

Compared performance of KNN, SVM, BPNN, CNN, Transfer Learning (retrain on Inception v3) on image classification problem. CNN is implemented with TensorFlow

Bio-Computing Platform featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

Library extending Jupyter notebooks to integrate with Apache TinkerPop and RDF SPARQL.

A collection of tools to collect and download various data.

Programming Music with Python, Sonic Pi and Supercollider

Python code for the fast bilateral solver

Auto-ReID and Other Person Re-Identification Projects

Deep Learning examples with Keras.

Malware Detection and Classification Using Machine Learning

Python/Keras implementation of integrated gradients presented in "Axiomatic Attribution for Deep Networks" for explaining any model defined in Keras framework.

Automatic image captioning model based on Caffe, using features from bottom-up attention.

This is the code for "Stock Market Prediction" by Siraj Raval on Youtube