6198 Open source projects that are alternatives of or similar to Readingbricks

BERT semantic search engine for searching literature research papers for coronavirus covid-19 in google colab

Train a Word2Vec model or LSA model, and Implement Conceptual Search\Semantic Search in Solr\Lucene - Simon Hughes Dice.com, Dice Tech Jobs

🎁 3,000,000+ Unsplash images made available for research and machine learning

北京邮电大学“网络搜索原理”课程资料(2019)

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

Natural Language Processing

Modular multitask reinforcement learning with policy sketches

Python for Finance (O'Reilly)

AIND Term 2 -- VUI Capstone Project

Adaptive Masked Proxies for Few Shot Semantic Segmentation

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

机器学习与深度学习算法示例

Implemented the YOLO algorithm for scene text detection in keras-tensorflow (No object detection API used) The code can be tweaked to train for a different object detection task using YOLO.

Python Cellular Sheaf Library

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

This repository contains IPython notebooks that I have written.

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

Exploring applications of deep learning to the world of wine

Some computer vision tutorials for my articles

公众号“无痛入门音乐科技”开源代码

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

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).

Udacity Data Engineering Nano Degree (DEND)

Code and instructions for making an animated map of Earth

CNN for intent classification task in a Chatbot

Beyond Accuracy: Behavioral Testing of NLP models with CheckList

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

The Hacker Within at the University of California - Berkeley

This repo will contain the resources available in my blog for learning

Pytorch implementation of the DeepDream computer vision algorithm

Repository which contains various scripts and work with various basketball statistics

https://plot.ly/dash/gallery/live-wind-data/

This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.

Credit Risk analysis by using Python and ML

capsule networks that achieves outstanding performance on the German traffic sign dataset

Deep learning tool to find brand logos in everyday pictures

MAGNet: Multi-agents control using Graph Neural Networks

Detecting emotions using MFCC features of human speech using Deep Learning

Original implementation of the paper "SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery" by Shion Honda et al.

UC Berkeley, W205 Data Engineering, 2018 Spring, Kevin Crook's supplement

FCOS: Fully Convolutional One-Stage Object Detection.

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

Models and Pipelines for the Spark NLP library

Multi-purpose tool for sound design and music production implemented in TensorFlow.

TabNet for fastai

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

GitHub Action for repo2docker

DEPRECATED: please see individual lesson repositories for current material.

A complete set of Recommender Systems techniques used in the Spotify Recsys Challenge 2018 developed by a team of MSc students in Politecnico di Milano.