Machine Learning – Breitschblog

Data Science Workshop

Data Science Workshop v. 28.5.2018, 13-15:30 pm Agenda: Introduction to TensorFlow and Scikit Learn We showed 4 building blocks and 8 discussion topics: Introduction (till slide 38) Methodology https://www.tensorflow.org/tutorials/ Practical Approach C:\maXbox\mX46210\DataScience\confusionlist\mnist_softmax21.py http://cs231n.github.io/python-numpy-tutorial/ : X:\1_Public\Documents\Data Science Workshops Best Introduction as Ranking Topics Discussion: Topics: – CaseCrunch UseCase – Start Values for Weights – How toContinue reading “Data Science Workshop”

A Sentiment API

maXbox Starter 82_2 – How to make a Sentiment Analysis, Max Kleiner “Yesterday I was clever, so I wanted to change the world. Today I am wise, so I am changing myself.” – Rumi As you way know, we went through the last magazine report on the BBC News feed, line by line in aContinue reading “A Sentiment API”

JSON Automation

Reading json data in maXbox could be easy. Json data can be read from a file or it could be a json web link. Let us first try to read the json from a web link. Const JsonUrl = ‘https://pomber.github.io/covid19/timeseries.json’; Let us first define the necessary packages “msxml2.xmlhttp and the JSON class”. Let us importContinue reading “JSON Automation”

MNIST Single Predict

MNIST Single Prediction We have set up a very simple SVC to classify the MNIST digits to make one single shoot predict. First we load the libraries and the dataset: A notebook you find at: https://github.com/maxkleiner/maXbox4/blob/master/MNISTSinglePredict.ipynb <class ‘sklearn.utils.Bunch’> 1797 samples Then we setup the Support Vector Classifier with the training data X and the targetContinue reading “MNIST Single Predict”

Board Game Regressor

Before we dive into machine learning, we’re going to explore a dataset, and figure out what might be interesting to predict. The dataset is from BoardGameGeek, and contains data on 80000 board games. Here’s a single boardgame on the site. This information was kindly scraped into csv format by Sean Beck, and can be downloadedContinue reading “Board Game Regressor”

Strange Circles

The use of prior time steps to predict the next time step is called the sliding window method. For short, it may be called the window method in some literature. In statistics and time series analysis, this is called a lag or lag method. The number of previous time steps is called the window widthContinue reading “Strange Circles”

maXbox4machine

Machine Learning models’ ultimate goal is making reliable predictions on new, unknown data. With this purpose in mind, we want our algorithm to capture relations in existing data and replicate them among new entries. At the same time, we do not want our algorithm to have, let’s say, prejudices because of the data it trainedContinue reading “maXbox4machine”