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.
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…
After working for a couple of years with Python and external dependencies I’ve ran again and again into the same kind of problems. Bad habits Say you have a global python installation under e.g. C:\Python36 on Windows. When you start working on your first python project you want to use external packages and you encounter…
During linting my code jshint gave me the “hint” that I should prefer dot notation over bracket notation. “testcase”: data.finding[“testcase”], [‘testcase’] is better written in dot notation. What is that? Accessing members with “.” is called “dot notation”. Accessing them with [] is called “bracket notation”.
Python is a dynamically typed language which makes it easy and fun to program. But sometimes -especially in bigger projects- it can become quite cumbersome when you just receive errors at run time. Given the hypothetical example where we define a function which multiplies integer: def multiply(a, b): return a * b print(multiply(“I”, “You”)) It…
Diving deeper into data science I started to brush up my knowledge about math especially statistics. The Mother of all Distributions The normal distribution was formulated by Carl Friedrich Gauß in 1809 and can be implemented in Python like the following : def normal_distribution_pdf(x, mu=0, sigma=1): sqrt_two_pi = math.sqrt(2*math.pi) return (1 / (sqrt_two_pi * sigma))…