wshBak

AI-for-Trading

Artificial Intelligence for Trading Nanodegree

algorithmic-trading-with-python

Source code for Algorithmic Trading with Python (2020) by Chris Conlan

apache-spark-best-practices-and-tuning

https://umbertogriffo.gitbook.io/apache-spark-best-practices-and-tuning/

AutoDD

Automatically does the "Due Diligence" for r/pennystocks

AutoDD_Rev2

An improved version of the original AutoDD

bayesianLSTM

Bayesian LSTM (Tensorflow)

databricks-training

databricks_training

databrickstraining-python

Databricks Academy Training - Python

deep-learning-illustrated

Deep Learning Illustrated (2019)

eat_tensorflow2_in_30_days

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

energy-ts-analysis

Jupyter notebook implementing time series forecasting of energy consumption data with different methods.

explainable-wind-power-forecast

Explainable Wind Power Forecast with Lale & AIX360

keras-multi-head

A wrapper layer for stacking layers horizontally

letslearnai

Resources and learning paths for Machine Learning

machine-learning-asset-management

Machine Learning in Asset Management

medium-ds-unsupervised-anomaly-detection-deepant-lstmae

Deep Learning based technique for Unsupervised Anomaly Detection using DeepAnT and LSTM Autoencoder

MLOps_Workshop

Azure MLOps

nlp_course

YSDA course in Natural Language Processing

nlpaug

Data augmentation for NLP

onlineNPCORR

Batch and online algorithms for nonparametric correlations such as Spearman's rank correlation and Kendall's tau correlation

Reddit-Stock-Trends

Fetch currently trending stocks on Reddit

spark-examples

RAPIDS Spark examples

Stock-Prediction-Models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

surpriver

Find big moving stocks before they move using machine learning and anomaly detection

textpack

Group thousands of similar spreadsheet or database text entries in seconds

TimeSeries_Seq2Seq

This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.

UnusualVolumeDetector

Gets the last 5 months of volume history for every ticker, and alerts you when a stock's volume exceeds 10 standard deviations from the mean within the last 3 days

wsb_scraper

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow