johnjdailey

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

Arabic_English

How to Learn Arabic or English

Backtrading-for-Amateurs

Simple backtrading strategy project using backtrader.

binance-official-api-docs-1

Official Documentation for the Binance US APIs and Streams

ds-med-cabinet

Cannabis Strain Recommendations using Natural Language Processing in a Neural Network.

ds-twitoff

Twitter app to load user tweets and predict which user would tweet a given input.

DS-Unit-4-Sprint-1-NLP

Notebooks for NLP, Vector Representations, Document Classification, Topic Modeling, and more.

DS-Unit-4-Sprint-2-Neural-Networks

Notebooks for Neural Networks, Keras, and Hyperparameter Tuning.

johnjdailey.github.io

JohnJDailey's Homepage

scrapy_noon_parfum_repo

Web scrape parfums from noon.com

johnjdailey/chainlink

node of the decentralized oracle network, bridging on and off-chain computation

johnjdailey/DS-Unit-4-Sprint-3-Deep-Learning

johnjdailey/arch

ARCH models in Python

johnjdailey/blog

Collection of the codes which are used on our blog at https://www.statworx.com/de/blog/

johnjdailey/CHIME-2

Next iteration of CHIME app - SIR model + Parameter Approximations

johnjdailey/CSPT13_DataStructures_gp

johnjdailey/CSPT13_IntroPython_GP

johnjdailey/Dash-by-Plotly

Interactive data analytics

johnjdailey/Data-Structures

johnjdailey/datadocs

Documentation for data enthusiasts

johnjdailey/DS

Data science component of Med Cabinet application.

johnjdailey/EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

johnjdailey/eiten

Statistical and Algorithmic Investing Strategies for Everyone

johnjdailey/Intro-Python-I

Introduction to Python basics

johnjdailey/Intro-Python-II

Second part of introduction to Python basics

johnjdailey/machinelearning

Machine learning and artificial intelligence

johnjdailey/mljar-supervised

:sparkles: Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning :rocket:

johnjdailey/plotly-tutorial

This Jupyter Notebook condenses the Plotly API into one easy to use document with examples

johnjdailey/Price-Forecaster

Forecasting the future prices of BTC and More using Machine and Deep Learning Models

johnjdailey/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

johnjdailey/pymarketstore

Python driver for MarketStore

johnjdailey/ReinforcementLearnigOptions

A DQN agent that optimally hedges an options portfolio. (Reinforcement Learning for Option Pricing

johnjdailey/sktime

A unified toolbox for machine learning with time series

johnjdailey/Sprint-Challenge--Data-Structures-Python

johnjdailey/Sprint-Challenge--Intro-Python

Intro to Python Sprint Challenge

johnjdailey/surpriver

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

johnjdailey/tqdm

A Fast, Extensible Progress Bar for Python and CLI

johnjdailey/tsfresh

Automatic extraction of relevant features from time series:

johnjdailey/vectorbt

Python library for backtesting and analyzing trading strategies at scale

johnjdailey/volatility-trading

A complete set of volatility estimators based on Euan Sinclair's Volatility Trading