### f-Strings in Python

Since Python 3.6 there is neat way to put variables into string, called f-strings: name = “joern” age = “37” print(f”My name is {name} and I’m {age}”)

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# Author Archives: Jörn

### f-Strings in Python

### Management 3.0 Workshop

### Confusion Matrix

### numpy random choice

### Classification: Precision and Recall

### UD120 – Intro to Machine Learning

### Lesson 2: Naive Bayes

### Lesson 3: Support Vector Machines

### /dev/night: Kubernetes Deep Dive

### Linear Algebra with numpy

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Since Python 3.6 there is neat way to put variables into string, called f-strings: name = “joern” age = “37” print(f”My name is {name} and I’m {age}”)

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.

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, 3],…

In the realms of Data Science you’ll encounter sooner or the later the terms “Precision” and “Recall”. But what do they mean? Clarification Living together with little kids You very often run into classification issues: My daughter really likes dogs, so seeing a dog is something positive. When she sees a normal dog e.g. a…

One part of my bucket list for 2018 is finishing the Udacity Course UD120: Intro to Machine Learning. The host of this course are Sebastian Thrun, ex-google-X and founder of Udacity and Katie Malone, creator of the Linear digressions podcast. The course consists of 17 lessons. Every lesson has a couple of hours of video…

Lesson 2 of the Udacity Course UD120 – Intro to Machine Learning deals with Naive Bayes classification.

The term Support Vector Machines or SVM is a bit misleading. It is just a name for a very clever algorithm invented by two Russians. in the 1960s. SVMs are used for classification and regression. SVM do that by finding a hyperplane between two classes of data which separates both classes best.

tl;dr: Awesome evening! /dev/night /dev/night is a series of tech talks organized and hosted by tradebyte, an e-commerce company from Ansbach. I’ve seen tradebyte as a sponsor of several barcamps, saw there ads for /dev/night and even had there sticker as my first sticker on my laptop. But I hadn’t made it to their event…

Numpy is a package for scientific computing in Python. It is blazing fast due to its implementation in C. It is often used together with pandas, matplotlib and Jupyter notebooks. Often these packages are referred to as the datascience stack. Installation You can install numpy via pip pip install numpy Basic Usage In the datascience…

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