To setup the SD Card on MacOS follow these steps Download the Raspbian Image Insert the SD-Card into the reader Open a terminal Find out the device’s name by typing diskutil list Erase the contents / format card to FAT32 sudo diskutil eraseDisk FAT32 RASPBIAN MBRFormat /dev/disk2 sudo diskutil unmountDisk /dev/disk2 Copy image to card…
Pandas is a data analyzing tool. Together with numpy and matplotlib it is part of the data science stack You can install it via pip install pandas Working with real data The data set we are using is the astronauts data set from kaggle: Download Data Set NASA Astronauts from Kaggle During this introduction we…
If You already read Python pip and virtualenv you are familiar with the way python handles requirements. but lo and behoild there is a new kid in town or actually two new kids on the block: Pipfile and Pipenv – both with with a capital “P”. If you are tired of creating and maintaining…
The Dark Ages The dark ages are the years between stopping playing with LEGO as a child and starting again to play again as an adult. In my case more than 20 years. Getting back to it When my older daughter turned 4, we decided to give her her first LEGO as a birthday present…
Applying for a data scientist job offer? Tired of writing the same old curriculum vitae? Why not showing your data visualization skills directly in your application? Generate Data Instead of pressing your data about education, employment and skills in a word-like document, put it in tables instead. E.g. use open office to create and edit…
Installation To work with OpenCV from python, you need to install it first. We additionally install numpy and matplotlib as well pip install opencv-python numpy matplotlib Reading Images from file After we import cv2 we can directly work with images like so: import cv2 img = cv2.imread(“doc_brown.png”) For showing the image, it is recommended to…
A cool new feature made its way into Python 3.7: Data classes. When You’ve already read my article about Lombok the concept isn’t so new at all: With the new decorator @dataclass You can save a huge amount of time because the methods __init__() __repr__() __eq__() are created for you! from dataclasses import dataclass @dataclass…
After trying a couple of times to get into a Management 3.0 training I finally had the chance to participate in a two day course in Nuremberg. Location The training was hosted at Ancud IT in downtown Nuremberg. The quiet working environment was awesome, the catering for the coffee breaks incredibly good. Kudo cards to…
Too confused of the confusion matrix? Let me bring some clarity into this topic! Let’s take the example from Precision and Recall: y_true = [“dog”, “dog”, “non-dog”, “non-dog”, “dog”, “dog”] y_pred = [“dog”, “non-dog”, “dog”, “non-dog”, “dog”, “non-dog”] When we look at the prediction we can count the correct and incorrect classifications: dog correctly classified…
With numpy you can easily create test data with random_integers and randint. numpy.random.randint(low, high=None, size=None, dtype=’l’) numpy.random.random_integers(low, high=None, size=None) random_integers includes the high boundary while randint does not. >>> import numpy as np >>> np.random.random_integers(5) 4 >>> np.random.random_integers(5, size=(5)) array([5, 3, 4, 1, 4]) >>> np.random.random_integers(5, size=(5, 4)) array([[2, 3, 3, 5], [1, 3, 1,…