The goal of this blog is to give a quick introduction into using TensorFlow Lite For Microcontrollers to create Audio Output with the help of the audio-tools library. Hallo World The starting point is the good overview provided by the “Hallo World” example of Tensorflow Lite which describes how to Read more…
In one of my latest Blogs I described how the API for an easy to use the micro_speech should look like. However I was struggling to make it work. So I decided to do some baby steps and make the existing example work first with my audio-tools library. We need Read more…
The staring point for doing speech recognition on an Arduino based board is TensorFlow Light For Microcontrollers with the example sketch called micro_speech! There are quite a few alternative Arduino Libraries for TensorFlow Light but honestly the situation is rather dire and I could not find any version which would Read more…
Financial KPIs can be used to drive investment decisions. So it was my goal to create a comprehensive set of KPIs across different dimensions. In this document we will use EDGAR to calculate KPIs to measure the following dimensions of a reporting company – Profitability – Liquidity – Efficiency – Read more…
Financial KPIs can be used to drive investment decisions. So it was my goal to create a comprehensive set of KPIs across different dimensions that are based on the information which can be determined from EDGAR: Profitibility Liquidity Efficiency Innovation Growth Leadereship Surprises In this document we demonstrate the approach Read more…
In this demo we show how to forecast if the NASDAQ-100 is moving up or down. We do this with the help of a Random Forrest Classifier from the Smile Machine Learning Framework. I tried to replicate the result from a research paper authored by Luckyson Khaidem, Snehanshu Saha, Sudeepa Read more…
In my last blog I demonstrated how to build a model that can predict if a stock is going up or down based on the news headlines using Spark MLLib. In this demo I will do the same – but with the help of OpenNLP. The solution consists of the following Read more…
In this blog we will demonstrate how we can predict if a stock is going up or down based on the news headlines. The solution consists of the following components: Spark MLLib (Machine Learning) My News-Digest (which I have described in my last blogs) Investor (we determine the stock prices Read more…
I am planning to use the DL4J Doc2Vec implementation for a sentiment analysis. However, I don’t want to start with an empty network but the staring point should be a pre-trained network: The initial trining should be done with the Sentiment140 dataset which can be found at https://www.kaggle.com/kazanova/sentiment140. It contains Read more…
The basic goal of a ‘sentiment analysis’ is to classify a given text into positive, negative or neutral. SentiWordNet is a lexical resource for opinion mining. It assigns sentiments to each synset of WordNet which makes it possible to “calculate” an overall sentiment for a text. A SentiWordNet implementation can Read more…