## Looking for a machine learning model that hits S&P 500 daily change using market breadth data, DIX, GEX, VIX.

This is the third version of a code I have started to write while learning the concepts of Machine Learning. Changes with respect the previous versions Shift(-1) have been removed for the SPX price, I consider is an error to add it. I have added data related to DIX, GEX (since 2011) and VIX (since … Read more

## Data analysis on market breadth data

This post is an exercise to learn how to predict using different data on a machine learning model. Background Market breadth data and indicators are very popular in the investment world. I find them useful, and as I know them, I will use them as basis to experiment machine learning models. Data Analysis I have … Read more

## Using Machine Learning to predict the S&P 500 price change, using the dark pool indicators Dix and Gex

This is the first version of an analysis I wanted to perform with the main purpose of learning. By this reason I have limited the number of input data and operations to the minimum. To do something different I will be looking for correlations between the two main dark pool indexes: DIX and GEX Indexes. … Read more

## How to solve Time Series problems with Machine Learning

There are different techniques or models to solve these type of problems. We can divide the type of models using this diagram: Traditional Time Series forecasting techniques Recursive: we can make predictions for tomorrow, the day after… to do the prediction of day #4 we will predict first #1, then #2, then #3 and then … Read more

## Uptime platform

The reason I like this type of solutions I studied electronic engineering and at the end of the degree I did a project to obtain the grade related to maintenance in an industry factory. I implemented a solution based on Lotus Notes where you could schedule the preventive maintenance activities, track the incidents, the inventory, … Read more

## Notes about convolutional neural networks

Let’s start with Wikipedia: In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural network, most commonly applied to analyze visual imagery. The name “convolutional neural network” indicates that the network employs a mathematical operation called convolution. The convolutional networks are a specialized type of neural networks that use convolution … Read more

## Increasing my knowledge on Machine Learning

This post covers different readings and learnings I’m working to gain knowledge on Machine Learning. At this moment, to me, there are 4 pillars of knowledge that I should gain when talking about Machine Learning. These are: Models & math’s knowledge. Software Programing: python (it’s the one I will use). How the machine learning initiatives … Read more

## Learning Data Visualization with Kaggle

I’m taking notes while I learn about data visualization on Kaggle.

## Introduction to Machine Learning in Kaggle

I’m going through the course “Intro to Machine Learning“, and I would like to keep some notes about it. My first machine learning code Model validation In almost all applications, the relevant measure of model quality is predictive accuracy. In other words, will the model’s predictions be close to what actually happens. Mean Absolute Error (MAE) … Read more

## Why is important DevOps for an organization that wants to implement Machine Learning initiatives?

Machine Learning projects come with a lot of complexity in terms of organization and this type of projects are not just to be a challenge for the consumption of infrastructure services, but it’s going to be a challenge to the ability of the organization to deliver in a reasonable speed. Let’s start with some basis … Read more