Pinned Repositories
AdvancedDataStruct
B-trees are traditionally used for database indexing. In this structure, a single node of a B-tree is usually stored in a separate memory pag
AdvOS-2016-JVM-research
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/
ASTParserTest-
You are to test ASTParser both in a unit test fashion and in an integration test fashion. Both kinds of test can be implemented as JUnit automated test suites, at least in principle.
AutoDD
Automatically does the "Due Diligence" for r/pennystocks
AutoDD_Rev2
An improved version of the original AutoDD
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
wshBak's Repositories
wshBak/AI-for-Trading
Artificial Intelligence for Trading Nanodegree
wshBak/algorithmic-trading-with-python
Source code for Algorithmic Trading with Python (2020) by Chris Conlan
wshBak/apache-spark-best-practices-and-tuning
https://umbertogriffo.gitbook.io/apache-spark-best-practices-and-tuning/
wshBak/AutoDD
Automatically does the "Due Diligence" for r/pennystocks
wshBak/AutoDD_Rev2
An improved version of the original AutoDD
wshBak/bayesianLSTM
Bayesian LSTM (Tensorflow)
wshBak/databricks-training
wshBak/databricks_training
wshBak/databrickstraining-python
Databricks Academy Training - Python
wshBak/deep-learning-illustrated
Deep Learning Illustrated (2019)
wshBak/eat_tensorflow2_in_30_days
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
wshBak/energy-ts-analysis
Jupyter notebook implementing time series forecasting of energy consumption data with different methods.
wshBak/explainable-wind-power-forecast
Explainable Wind Power Forecast with Lale & AIX360
wshBak/keras-multi-head
A wrapper layer for stacking layers horizontally
wshBak/letslearnai
Resources and learning paths for Machine Learning
wshBak/machine-learning-asset-management
Machine Learning in Asset Management
wshBak/medium-ds-unsupervised-anomaly-detection-deepant-lstmae
Deep Learning based technique for Unsupervised Anomaly Detection using DeepAnT and LSTM Autoencoder
wshBak/MLOps_Workshop
Azure MLOps
wshBak/nlp_course
YSDA course in Natural Language Processing
wshBak/nlpaug
Data augmentation for NLP
wshBak/onlineNPCORR
Batch and online algorithms for nonparametric correlations such as Spearman's rank correlation and Kendall's tau correlation
wshBak/Reddit-Stock-Trends
Fetch currently trending stocks on Reddit
wshBak/spark-examples
RAPIDS Spark examples
wshBak/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
wshBak/surpriver
Find big moving stocks before they move using machine learning and anomaly detection
wshBak/textpack
Group thousands of similar spreadsheet or database text entries in seconds
wshBak/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.
wshBak/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
wshBak/wsb_scraper
wshBak/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