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Resources for developers using Python for scientific computing and quantitative analysis

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Archives for September 2020

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Machine Learning from Scratch github.io

Published September 20, 2020 under Data Science

Machine Learning from Scratch

This book covers the building blocks of the most common methods in machine learning. This set of methods is like a toolbox for machine learning engineers. Those entering the field of machine learning should feel comfortable with this toolbox so they have the right tool for a variety of tasks. Each chapter in this book corresponds to a single machine learning method or group of methods. In other words, each chapter focuses on a single tool within the ML toolbox.

Ebook, Free, Machine Learning

Algorithmic Trading Using Logistic Regression handsoffinvesting.com

Published September 20, 2020 under Machine Learning

Algorithmic Trading Using Logistic Regression

In order to implement an algorithmic trading strategy though, you have to first narrow down a list of stocks that you want to analyze. This walk-through provides an automated process (using python and logistic regression) for determining the best stocks to algo-trade.

I will dive deeper into the logic and code below, but here is a high-level overview of the process:

  1. Import the historical data of every stock using yahoo finance.
  2. Pull in over 32 technical indicators for each stock using the technical analysis library.
  3. Perform a logistic regression on each stock using 5, 30, and 60 day observation time periods.
  4. Interpret the results.

Algorithmic Trading, Quant Trading

Array programming with NumPy nature.com

Published September 20, 2020 under Python

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. 

Numerical Methods, Numpy

Time-Series Forecasting with TensorFlow 2.0 theclickreader.com

Published September 7, 2020 under Machine Learning

In this tutorial, you will be learning how to build powerful time-series forecasting model of your own using various kinds of deep learning algorithms such as Dense Neural Networks (DNN), Convolutional Neural Network (CNN) and Recurrent Neural Networks (RNN). Also, this course is an elaboration of the time-series forecasting tutorial by TensorFlow.

Python, Time Series Analysis

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