Py4fi2nd - Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

Related tags

Deep Learningpy4fi2nd
Overview

Python for Finance (2nd ed., O'Reilly)

This repository provides all Python codes and Jupyter Notebooks of the book Python for Finance -- Mastering Data-Driven Finance (2nd edition) by Yves Hilpisch.

Visit the book page of O'Reilly under http://bit.ly/python-finance-2e or order the book under https://www.amazon.com/Python-Finance-Mastering-Data-Driven/dp/1492024333/.

The codes of the book are based on Python 3.7. The codes presented in this Github repository are tested for Python 3.6 since at the time of creating it, TensorFlow was not yet compatible with Python 3.7. Once this has happened, appropriate changes (e.g. to the conda yaml file, see below) will be made.

Python Packages

There is a yaml file for the installation of required Python packages in the repository. This is to be used with the conda package manager (see https://conda.io/docs/user-guide/tasks/manage-environments.html). If you do not have Miniconda or Anaconda installed, we recommend to install Miniconda 3.7 first (see https://conda.io/miniconda.html).

After you have cloned the repository, do on the shell (currently works on Mac OS):

cd py4fi2nd
conda env create -f py4fi2nd.yml
source activate py4fi2nd
jupyter notebook

Then you can navigate to the Jupyter Notebook files and get started.

Quant Platform

You can immediately use all codes and Jupyter Notebooks by registering on the Quant Platform under http://py4fi.pqp.io.

Python for Finance Training & University Certificate

Check out our Python for Finance & Algorithmic Trading online trainings under http://training.tpq.io.

Check out also our University Certificate Program in Python for Algorithmic Trading under http://certificate.tpq.io.

Company Information

© Dr. Yves J. Hilpisch | The Python Quants GmbH

The Quant Platform (http://pqp.io) and all codes/Jupyter notebooks come with no representations or warranties, to the extent permitted by applicable law.

http://tpq.io | [email protected] | http://twitter.com/dyjh

Quant Platform | http://pqp.io

Derivatives Analytics with Python (Wiley Finance) | http://dawp.tpq.io

Python for Finance (O'Reilly) | http://pff.tpq.io

Python for Finance Online Training | http://training.tpq.io

University Certificate in Python for Algorithmic Trading | http://certificate.tpq.io

Owner
Yves Hilpisch
CEO The Python Quants & The AI Machine | Adjunct Professor of Computational Finance | Python, AI, Finance & Algorithmic Trading
Yves Hilpisch
Learning to Prompt for Vision-Language Models.

CoOp Paper: Learning to Prompt for Vision-Language Models Authors: Kaiyang Zhou, Jingkang Yang, Chen Change Loy, Ziwei Liu CoOp (Context Optimization)

Kaiyang 679 Jan 04, 2023
TCTrack: Temporal Contexts for Aerial Tracking (CVPR2022)

TCTrack: Temporal Contexts for Aerial Tracking (CVPR2022) Ziang Cao and Ziyuan Huang and Liang Pan and Shiwei Zhang and Ziwei Liu and Changhong Fu In

Intelligent Vision for Robotics in Complex Environment 100 Dec 19, 2022
Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data.

Deep Learning Dataset Maker Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data. How to use Down

deepbands 25 Dec 15, 2022
Bayesian Optimization Library for Medical Image Segmentation.

bayesmedaug: Bayesian Optimization Library for Medical Image Segmentation. bayesmedaug optimizes your data augmentation hyperparameters for medical im

Şafak Bilici 7 Feb 10, 2022
This game was designed to encourage young people not to gamble on lotteries, as the probablity of correctly guessing the number is infinitesimal!

Lottery Simulator 2022 for Web Launch Application Developed by John Seong in Ontario. This game was designed to encourage young people not to gamble o

John Seong 2 Sep 02, 2022
MLSpace: Hassle-free machine learning & deep learning development

MLSpace: Hassle-free machine learning & deep learning development

abhishek thakur 293 Jan 03, 2023
Make your own game in a font!

Project structure. Included is a suite of tools to create font games. Tutorial: For a quick tutorial about how to make your own game go here For devel

Michael Mulet 125 Dec 04, 2022
EMNLP 2021: Single-dataset Experts for Multi-dataset Question-Answering

MADE (Multi-Adapter Dataset Experts) This repository contains the implementation of MADE (Multi-adapter dataset experts), which is described in the pa

Princeton Natural Language Processing 68 Jul 18, 2022
Use deep learning, genetic programming and other methods to predict stock and market movements

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

Linda MacPhee-Cobb 386 Jan 03, 2023
Doing fast searching of nearest neighbors in high dimensional spaces is an increasingly important problem

Benchmarking nearest neighbors Doing fast searching of nearest neighbors in high dimensional spaces is an increasingly important problem, but so far t

Erik Bernhardsson 3.2k Jan 03, 2023
An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

Meta Research 141 Jan 07, 2023
[ICCV2021] Learning to Track Objects from Unlabeled Videos

Unsupervised Single Object Tracking (USOT) 🌿 Learning to Track Objects from Unlabeled Videos Jilai Zheng, Chao Ma, Houwen Peng and Xiaokang Yang 2021

53 Dec 28, 2022
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).

Knowledge Informed Machine Learning using a Weibull-based Loss Function Exploring the concept of knowledge-informed machine learning with the use of a

Tim 43 Dec 14, 2022
Conformer: Local Features Coupling Global Representations for Visual Recognition

Conformer: Local Features Coupling Global Representations for Visual Recognition (arxiv) This repository is built upon DeiT and timm Usage First, inst

Zhiliang Peng 378 Jan 08, 2023
Code for CVPR 2021 paper TransNAS-Bench-101: Improving Transferrability and Generalizability of Cross-Task Neural Architecture Search.

TransNAS-Bench-101 This repository contains the publishable code for CVPR 2021 paper TransNAS-Bench-101: Improving Transferrability and Generalizabili

Yawen Duan 17 Nov 20, 2022
Equivariant GNN for the prediction of atomic multipoles up to quadrupoles.

Equivariant Graph Neural Network for Atomic Multipoles Description Repository for the Model used in the publication 'Learning Atomic Multipoles: Predi

16 Nov 22, 2022
Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure.

Event Queue Dialect Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure. Motivation The m

Cornell Capra 23 Dec 08, 2022
[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"

KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl

Hyeongseok Son 50 Dec 29, 2022
ZSL-KG is a general-purpose zero-shot learning framework with a novel transformer graph convolutional network (TrGCN) to learn class representation from common sense knowledge graphs.

ZSL-KG is a general-purpose zero-shot learning framework with a novel transformer graph convolutional network (TrGCN) to learn class representa

Bats Research 94 Nov 21, 2022
Official Pytorch implementation of 'RoI Tanh-polar Transformer Network for Face Parsing in the Wild.'

Official Pytorch implementation of 'RoI Tanh-polar Transformer Network for Face Parsing in the Wild.'

Jie Shen 125 Jan 08, 2023