In this post, we will be training the Twitter sentiment corpus using a Keras deep neural network. This is a famous dataset with labeled sentiment on over a million tweets and coming in at a hefty 150mb.

There are many ways to train a sentiment anlaysis model on the twitter corpus, and in this tutorial, we will be focusing on a deep neural network.

If you want to follow along with the tut...

Since the 2008 recession, stocks have been on the longest bull run in U.S. history, carried mainly by the technology sector.

2018 has been interesting on a macroeconomic scale: the U.S. Dollar Index has strengthened, the Argentine Peso has plummeted, Crude oil is in the middle of a resurgence, the yield curve has narrowed, and the U.S. stock market has strengthened in relation to intern...

There are a select group of people out there who have monthly mortgages on par with the average cost of a house in the United States.

A 200,000 a month mortgage naturally stirs the curiosity: why would you take a loan instead of paying cash, why would a bank underwrite such a loan, where are these houses, and who are these people? I'll use this post to describe the rationale for both side...

It is universally agreed by US intelligence agencies that the Russians had a hand influencing the 2016 election using popular social media platforms. I am not interested in making this a political debate one way or the other.

I wanted to use some NLP tools to find some statistics and meta data about the tweets to see if they have any distinguishing characteristics, and whether some simple anal...

LSTM's, or Long short-term memory units, are a type of recurrent neural network that are useful in processing sequential data. They keep their hidden state over time, and so have a form of memory.

If you learn one thing from this post, it is that a long short term memory network as simple as the one in this article is not that great at predicting something as random as the swings, and often t...

If you are interested in predicting the future movements of a dataset, you are going to need to setup the data so that it conforms to a certain format for time series training.

This article is not going to be a thorough treatment about time series analysis, so concepts like seasonality and other factors that might affect the accuracy of time series prediction are not in the purview of this tut...

"fortify yourself in eyes of men
this i witness call the fools of time
with aprils firstborn flowers and all her fading sweets
and live no hatred in thine eye
use power with power and slay me not by art"

Remember those lines? Hopefully not, because they have never graced a page. The lines above were randomly generated from a Markov model, traine...

This will be a quick lesson on downloading and running a few queries in kdb+, a lightweight (seriously the binary download is 300kb) database that is used in a variety of applications where performance for vast amounts of data is critical. From quant firms trading financial securities to F1 teams needing streaming telemetry data for their race cars, kdb+ is used in a variety of highly demanding real ...

Sympy is a library for doing symbolic math with Python. Python is a very flexible language, but it doesn't come built in with symbolic math functions. Beyond manipulating numbers, you may want to do operations, factorize, or even take the derivative or integral of a function.

This tutorial is to get your feet wet with the syntax and notation of Sympy.

If you want to take this tutorial...

In any given year, there will be assets that are set to reprice, and there are liabilities set to reprice. The difference between these two amounts as a percentage of total assets is called the one-year gap ratio.

This ratio is particularly interesting for investors studying banks in a rising interest rate environment like the one we are currently experiencing in 2018, with the fed signaling ...

In this post, I'm going to post five lists of 50 or so words obtained using natural language processing. These lists are words from select works by famous novelists.

Sometimes the list came from one seminal work, and other times the list was generated from multiple popular works from the mystery authors in question. I was particularly interested in words that the author used in more than on...

If you looked at the graphs on the image to the left, you would think that the underlying data points wouldn't share much in common. However, all three data groups share the same mean value. That's right, the average value for these three disparate visual representations are all the same. Not only that, but they also have the same Pearson correlation coefficient.

Pretty neat, right? Well, Fra...

Welcome to my new blog, Data Dreams. I created this blog to share my passion for data science. In this blog, I will post tutorials on AI, machine learning, natural language processing, statistics, finance, econometrics, and general topics dealing with data science itself.

Data Dreams was named simply for my passion and dreams about data. Besides tutorials, I hope to provide interesting artic...