6108 Open source projects that are alternatives of or similar to Tweet Stance Prediction

Python for Finance (O'Reilly)

💡 Repo of learning notes in DRL and DL, theory, codes, models and notes maybe.

This repository contains IPython notebooks that I have written.

Udacity capstone project: Kaggle competition on house prices prediction using advanced regression techniques

AIND Term 2 -- VUI Capstone Project

Code for the paper "Spatio-Temporal Neural Networks for Space-Time Series Modeling and Relations Discovery"

Exploring applications of deep learning to the world of wine

Official implementation of "Desinging an Encoder for StyleGAN Image Manipulation" https://arxiv.org/abs/2102.02766

机器学习与深度学习算法示例

Adaptive Masked Proxies for Few Shot Semantic Segmentation

Understanding facial beauty with deep learning.

公众号“无痛入门音乐科技”开源代码

Repository for benchmarking graph neural networks

Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).

course materials for introduction to deep learning 2020

Models and Pipelines for the Spark NLP library

Material and note of the course of Applied ML in Python

GitHub Action for repo2docker

Python Cellular Sheaf Library

Faster-RCNN based on Densecap(deprecated)

import code from IJulia Jupyter notebooks into Julia programs

Game Theory and Python, a workshop investigating repeated games using the prisoner's dilemma

Modular multitask reinforcement learning with policy sketches

비전공생도 한눈에 이해하는 딥러닝 자료모음

Code for my EMNLP 2018 paper "SimpleQuestions Nearly Solved: A New Upperbound and Baseline Approach"

[repo not maintained] Check out https://diffgram.com if you want to build a visual intelligence

Code for reproducing the results from the paper Few Shot Text Classification with a Human in the Loop

《Python Cookbook》 3rd Edition Translation

Experiments with Deep Learning

Implementation of the paper "Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching"

[BA project] Dynamic Pricing Optimization for Airbnb listing to optimize yearly profit for host. Use Clustering for competitive analysis, kNN regression for demand forecasting, and find dynamic optimal price with Optimization model.

基于李笑来的那本自学是一门手艺的书，然后里面有自己修改的痕迹，以及更多的资料。

Reducing the size of convolutional neural networks

Credit Risk analysis by using Python and ML

An LSTM Autoencoder for rare event classification

Place for resources used during the Mordor Detection hackathon event featuring APT29 ATT&CK evals datasets

Repository for reading Pascal VOC data in Python, rather than requiring MATLAB to read the XML files.

Code release for Hu et al. Segmentation from Natural Language Expressions. in ECCV, 2016

Deep learning tutorial for PyData

A structured collection of tagged notes about machine learning theory and practice endowed with search infrastructure that allows users to read requested info only.

Detecting emotions using MFCC features of human speech using Deep Learning

Distributed deep learning on Hadoop and Spark clusters.

A community run, 5-day PyTorch Deep Learning Bootcamp

Basics of programming: algorithms, data structures, object oriented programming

Atom notebook

Videos of deep learning optimizers moving on 3D problem-landscapes

AI-ON Consciousness Prior

Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

Gamified tutorial for the QISKit quantum SDK

A non-sampling profiler purpose built to measure and optimize performance of ultra low latency/real time systems

Deliverable: This Jupyter notebook will help aspiring data scientists learn and practice the necessary python code needed for many data science projects.

Book sample (AI Machine-learning Deep-learning)

Implementation of Fast-SCNN using Tensorflow 2.0

An RNN implementation to generate music