Just a place to write
If you have a mine, the cost of obtaining a kilo of gold, aluminum, cooper or whatever, they all measure the cost of obtaining a kilo of the target element. With the machine learning projects, the situation is similar, and the definition of cost of data exploitation is something that should be defined from early … Read more
During Q2 one of the topics have been to learn about Machine Learning on Kaggle. I started on kaggle as platform to use their courses, their community and I finished doing some finance examples on Google CoLab. I’m not a sofwtare developer neither a data scientific, but I am willing to learn all the concepts of machine learning … Read more
This post gather the analysis of data done with market breadth data, VIX, DIX and GEX. They are moved into a Long Short Term Memory (LSTM) neural network, that is a recurrent neural network. You can check the code and read how the whole thing is done. Input data The used features as input are: … Read more
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
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
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
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
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
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
I’m taking notes while I learn about data visualization on Kaggle.