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active_portfolio_management

A crash course on understanding ( at a surface level) what is active portfolio management and how an over simplistic hypothetical portfolio signal might be built

ai-daily

AI Daily aggregates updates and news from subreddits, Twitter, and Gelt to create a comprehensive daily coverage of all AI-related news and updates. This AI-powered tool covers a wide range of topics, including breakthroughs, front-page news, rants, gossip, what's new, and more.

anomaliesinoptions

In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.

bert

TensorFlow code and pre-trained models for BERT

code4goal-resume-parser

Solution for Code4Goal challenge

dash-oil-and-gas-demo

Dash Demo App - New York Oil and Gas

dptoolkit

The Data Productivity Toolkit is a collection of linux command-line tools designed to facilitate the analysis of text-based data sets.

kaggle_crowdflower

1st Place Solution for Search Results Relevance Competition on Kaggle (https://www.kaggle.com/c/crowdflower-search-relevance)

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

prettymapp

🖼️ Create beautiful maps from OpenStreetMap data in a streamlit webapp

prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

python-books

My Python Book Collection

python-fire

Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

r-zoo

Clone of 'zoo' time-series R package from RForge

resp

resume-parser

Analyze, score and rank a collection of PDF resumes using machine learning

resumeparser

Resume Parser using rule and machine-learning based approach. Developed using framework provided by GATE

resumeparser-1

A script to parse PDF resumes, extract contact information, and check for required terms

stanford-cs-221-artificial-intelligence

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

tsfresh

Automatic extraction of relevant features from time series:

utilities

xgboost

Large-scale and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, on single node, hadoop yarn and more.