Examples and code for the Practical Machine Learning workshop series

Overview

Practical Machine Learning Workshop Series

Practical Machine Learning for Quantitative Finance

  • Post conference workshop at the WBS Spring Conference
  • Date: Monday 29th & Tuesday 30th March 2021
  • Time: EDT: 9-11am / BST: 2-4pm / CEST: 3-5pm

Agenda

We will focus on two concepts in machine learning that hold great promise for quant finance:

  • Regression models on Day 1
  • Generative models on Day 2

Each day, we will discuss theory during the first hour, and then use what we learned to solve practical quant finance problems during the second hour.

During the practice sessions, we will review, update and run code on Colab and AWS. Participants are welcome to just observe, or if desired also participate in writing or running the code (participation is strictly optional). The code will be available on GitHub after the workshop.

Day 1 – Regression Models

  • Regression model types
  • Feedforward networks
  • Autoencoders

Practice session: Estimation of Drift in Real-World Measure

Day 2 – Generative Models

  • Generative model types
  • Joint and Conditional Probabilities
  • Gibbs sampling

Practice session: Estimation of Probability in Real-World Measure

A naive Bayes model for cancer classification using a set of documents

Naivebayes text classifcation model for cancer and noncancer documents Author: Alex King Purpose Requirements/files included How to use 1. Purpose The

Alex W King 1 Nov 24, 2021
Conducted ANOVA and Logistic regression analysis using matplot library to visualize the result.

Intro-to-Data-Science Conducted ANOVA and Logistic regression analysis. Project ANOVA The main aim of this project is to perform One-Way ANOVA analysi

Chris Yuan 1 Feb 06, 2022
A linear regression model for house price prediction

Linear_Regression_Model A linear regression model for house price prediction. This code is using these packages, so please make sure your have install

ShawnWang 1 Nov 29, 2021
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

2 Jun 14, 2022
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learn

Vowpal Wabbit 8.1k Dec 30, 2022
Uplift modeling and causal inference with machine learning algorithms

Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang

Uber Open Source 3.7k Jan 07, 2023
The Ultimate FREE Machine Learning Study Plan

The Ultimate FREE Machine Learning Study Plan

Patrick Loeber (Python Engineer) 2.5k Jan 05, 2023
Python module for data science and machine learning users.

dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu

Emmanuel ASIFIWE 1 Nov 23, 2021
Simple linear model implementations from scratch.

Hand Crafted Models Simple linear model implementations from scratch. Table of contents Overview Project Structure Getting started Citing this project

Jonathan Sadighian 2 Sep 13, 2021
My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data

kNN-vs-RFR My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data In many areas, rental bikes have been launched to

1 Oct 28, 2021
Simplify stop motion animation with machine learning.

Simplify stop motion animation with machine learning.

Nick Bild 25 Sep 15, 2022
healthy and lesion models for learning based on the joint estimation of stochasticity and volatility

health-lesion-stovol healthy and lesion models for learning based on the joint estimation of stochasticity and volatility Reference please cite this p

5 Nov 01, 2022
PySpark + Scikit-learn = Sparkit-learn

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

Lensa 1.1k Jan 04, 2023
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

PyCaret 6.7k Jan 08, 2023
GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms

Generator of Rad Names from Decent Paper Acronyms

264 Nov 08, 2022
Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis.

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics

Facebook Research 4.1k Dec 29, 2022
Uber Open Source 1.6k Dec 31, 2022
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters

Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM

Joaquín Amat Rodrigo 297 Jan 09, 2023
This repository demonstrates the usage of hover to understand and supervise a machine learning task.

Hover Example Apps (works out-of-the-box on Binder) This repository demonstrates the usage of hover to understand and supervise a machine learning tas

Pavel 43 Dec 03, 2021
A Python implementation of the Robotics Toolbox for MATLAB

Robotics Toolbox for Python A Python implementation of the Robotics Toolbox for MATLAB® GitHub repository Documentation Wiki (examples and details) Sy

Peter Corke 1.2k Jan 07, 2023